graph in research paper

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How to Use Tables & Graphs in a Research Paper

It might not seem very relevant to the story and outcome of your study, but how you visually present your experimental or statistical results can play an important role during the review and publication process of your article. A presentation that is in line with the overall logical flow of your story helps you guide the reader effectively from your introduction to your conclusion. 

If your results (and the way you organize and present them) don’t follow the story you outlined in the beginning, then you might confuse the reader and they might end up doubting the validity of your research, which can increase the chance of your manuscript being rejected at an early stage. This article illustrates the options you have when organizing and writing your results and will help you make the best choice for presenting your study data in a research paper.

Why does data visualization matter?

Your data and the results of your analysis are the core of your study. Of course, you need to put your findings and what you think your findings mean into words in the text of your article. But you also need to present the same information visually, in the results section of your manuscript, so that the reader can follow and verify that they agree with your observations and conclusions. 

The way you visualize your data can either help the reader to comprehend quickly and identify the patterns you describe and the predictions you make, or it can leave them wondering what you are trying to say or whether your claims are supported by evidence. Different types of data therefore need to be presented in different ways, and whatever way you choose needs to be in line with your story. 

Another thing to keep in mind is that many journals have specific rules or limitations (e.g., how many tables and graphs you are allowed to include, what kind of data needs to go on what kind of graph) and specific instructions on how to generate and format data tables and graphs (e.g., maximum number of subpanels, length and detail level of tables). In the following, we will go into the main points that you need to consider when organizing your data and writing your result section .

Table of Contents:

Types of data , when to use data tables .

• When to Use Data Graphs 

Common Types of Graphs in Research Papers 

Journal guidelines: what to consider before submission.

Depending on the aim of your research and the methods and procedures you use, your data can be quantitative or qualitative. Quantitative data, whether objective (e.g., size measurements) or subjective (e.g., rating one’s own happiness on a scale), is what is usually collected in experimental research. Quantitative data are expressed in numbers and analyzed with the most common statistical methods. Qualitative data, on the other hand, can consist of case studies or historical documents, or it can be collected through surveys and interviews. Qualitative data are expressed in words and needs to be categorized and interpreted to yield meaningful outcomes. 

Quantitative data example: Height differences between two groups of participants Qualitative data example: Subjective feedback on the food quality in the work cafeteria

Depending on what kind of data you have collected and what story you want to tell with it, you have to find the best way of organizing and visualizing your results.

When you want to show the reader in detail how your independent and dependent variables interact, then a table (with data arranged in columns and rows) is your best choice. In a table, readers can look up exact values, compare those values between pairs or groups of related measurements (e.g., growth rates or outcomes of a medical procedure over several years), look at ranges and intervals, and select specific factors to search for patterns. 

Tables are not restrained to a specific type of data or measurement. Since tables really need to be read, they activate the verbal system. This requires focus and some time (depending on how much data you are presenting), but it gives the reader the freedom to explore the data according to their own interest. Depending on your audience, this might be exactly what your readers want. If you explain and discuss all the variables that your table lists in detail in your manuscript text, then you definitely need to give the reader the chance to look at the details for themselves and follow your arguments. If your analysis only consists of simple t-tests to assess differences between two groups, you can report these results in the text (in this case: mean, standard deviation, t-statistic, and p-value), and do not necessarily need to include a table that simply states the same numbers again. If you did extensive analyses but focus on only part of that data (and clearly explain why, so that the reader does not think you forgot to talk about the rest), then a graph that illustrates and emphasizes the specific result or relationship that you consider the main point of your story might be a better choice.

When to Use Data Graphs

Graphs are a visual display of information and show the overall shape of your results rather than the details. If used correctly, a visual representation helps your (or your reader’s) brain to quickly understand large amounts of data and spot patterns, trends, and exceptions or outliers. Graphs also make it easier to illustrate relationships between entire data sets. This is why, when you analyze your results, you usually don’t just look at the numbers and the statistical values of your tests, but also at histograms, box plots, and distribution plots, to quickly get an overview of what is going on in your data.

Line graphs

When you want to illustrate a change over a continuous range or time, a line graph is your best choice. Changes in different groups or samples over the same range or time can be shown by lines of different colors or with different symbols.

Example: Let’s collapse across the different food types and look at the growth of our four fish species over time.

You should use a bar graph when your data is not continuous but divided into categories that are not necessarily connected, such as different samples, methods, or setups. In our example, the different fish types or the different types of food are such non-continuous categories.

Example: Let’s collapse across the food types again and also across time, and only compare the overall weight increase of our four fish types at the end of the feeding period.

Scatter plots

Scatter plots can be used to illustrate the relationship between two variables — but note that both have to be continuous. The following example displays “fish length” as an additional variable–none of the variables in our table above (fish type, fish food, time) are continuous, and they can therefore not be used for this kind of graph. 

As you see, these example graphs all contain less data than the table above, but they lead the reader to exactly the key point of your results or the finding you want to emphasize. If you let your readers search for these observations in a big table full of details that are not necessarily relevant to the claims you want to make, you can create unnecessary confusion. Most journals allow you to provide bigger datasets as supplementary information, and some even require you to upload all your raw data at submission. When you write up your manuscript, however, matching the data presentation to the storyline is more important than throwing everything you have at the reader. 

Don’t forget that every graph needs to have clear x and y axis labels , a title that summarizes what is shown above the figure, and a descriptive legend/caption below. Since your caption needs to stand alone and the reader needs to be able to understand it without looking at the text, you need to explain what you measured/tested and spell out all labels and abbreviations you use in any of your graphs once more in the caption (even if you think the reader “should” remember everything by now, make it easy for them and guide them through your results once more). Have a look at this article if you need help on how to write strong and effective figure legends .

Even if you have thought about the data you have, the story you want to tell, and how to guide the reader most effectively through your results, you need to check whether the journal you plan to submit to has specific guidelines and limitations when it comes to tables and graphs. Some journals allow you to submit any tables and graphs initially (as long as tables are editable (for example in Word format, not an image) and graphs of high enough resolution. 

Some others, however, have very specific instructions even at the submission stage, and almost all journals will ask you to follow their formatting guidelines once your manuscript is accepted. The closer your figures are already to those guidelines, the faster your article can be published. This PLOS One Figure Preparation Checklist is a good example of how extensive these instructions can be – don’t wait until the last minute to realize that you have to completely reorganize your results because your target journal does not accept tables above a certain length or graphs with more than 4 panels per figure. 

Some things you should always pay attention to (and look at already published articles in the same journal if you are unsure or if the author instructions seem confusing) are the following:

• How many tables and graphs are you allowed to include?
• What file formats are you allowed to submit?
• Are there specific rules on resolution/dimension/file size?
• Should your figure files be uploaded separately or placed into the text?
• If figures are uploaded separately, do the files have to be named in a specific way?
• Are there rules on what fonts to use or to avoid and how to label subpanels?
• Are you allowed to use color? If not, make sure your data sets are distinguishable.

If you are dealing with digital image data, then it might also be a good idea to familiarize yourself with the difference between “adjusting” for clarity and visibility and image manipulation, which constitutes scientific misconduct .  And to fully prepare your research paper for publication before submitting it, be sure to receive proofreading services , including journal manuscript editing and research paper editing , from Wordvice’s professional academic editors .

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Tables and Figures

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Note:  This page reflects the latest version of the APA Publication Manual (i.e., APA 7), which released in October 2019. The equivalent resources for the older APA 6 style  can be found at this page  as well as at this page (our old resources covered the material on this page on two separate pages).

The purpose of tables and figures in documents is to enhance your readers' understanding of the information in the document; usually, large amounts of information can be communicated more efficiently in tables or figures. Tables are any graphic that uses a row and column structure to organize information, whereas figures include any illustration or image other than a table.

General guidelines

Visual material such as tables and figures can be used quickly and efficiently to present a large amount of information to an audience, but visuals must be used to assist communication, not to use up space, or disguise marginally significant results behind a screen of complicated statistics. Ask yourself this question first: Is the table or figure necessary? For example, it is better to present simple descriptive statistics in the text, not in a table.

Relation of Tables or Figures and Text

Because tables and figures supplement the text, refer in the text to all tables and figures used and explain what the reader should look for when using the table or figure. Focus only on the important point the reader should draw from them, and leave the details for the reader to examine on their own.

Documentation

If you are using figures, tables and/or data from other sources, be sure to gather all the information you will need to properly document your sources.

Integrity and Independence

Each table and figure must be intelligible without reference to the text, so be sure to include an explanation of every abbreviation (except the standard statistical symbols and abbreviations).

Organization, Consistency, and Coherence

Number all tables sequentially as you refer to them in the text (Table 1, Table 2, etc.), likewise for figures (Figure 1, Figure 2, etc.). Abbreviations, terminology, and probability level values must be consistent across tables and figures in the same article. Likewise, formats, titles, and headings must be consistent. Do not repeat the same data in different tables.

Data in a table that would require only two or fewer columns and rows should be presented in the text. More complex data is better presented in tabular format. In order for quantitative data to be presented clearly and efficiently, it must be arranged logically, e.g. data to be compared must be presented next to one another (before/after, young/old, male/female, etc.), and statistical information (means, standard deviations, N values) must be presented in separate parts of the table. If possible, use canonical forms (such as ANOVA, regression, or correlation) to communicate your data effectively.

A generic example of a table with multiple notes formatted in APA 7 style.

Elements of Tables

Number all tables with Arabic numerals sequentially. Do not use suffix letters (e.g. Table 3a, 3b, 3c); instead, combine the related tables. If the manuscript includes an appendix with tables, identify them with capital letters and Arabic numerals (e.g. Table A1, Table B2).

Like the title of the paper itself, each table must have a clear and concise title. Titles should be written in italicized title case below the table number, with a blank line between the number and the title. When appropriate, you may use the title to explain an abbreviation parenthetically.

Comparison of Median Income of Adopted Children (AC) v. Foster Children (FC)

Keep headings clear and brief. The heading should not be much wider than the widest entry in the column. Use of standard abbreviations can aid in achieving that goal. There are several types of headings:

• Stub headings describe the lefthand column, or stub column , which usually lists major independent variables.
• Column headings describe entries below them, applying to just one column.
• Column spanners are headings that describe entries below them, applying to two or more columns which each have their own column heading. Column spanners are often stacked on top of column headings and together are called decked heads .
• Table Spanners cover the entire width of the table, allowing for more divisions or combining tables with identical column headings. They are the only type of heading that may be plural.

All columns must have headings, written in sentence case and using singular language (Item rather than Items) unless referring to a group (Men, Women). Each column’s items should be parallel (i.e., every item in a column labeled “%” should be a percentage and does not require the % symbol, since it’s already indicated in the heading). Subsections within the stub column can be shown by indenting headings rather than creating new columns:

Chemical Bonds

     Ionic

     Covalent

     Metallic

The body is the main part of the table, which includes all the reported information organized in cells (intersections of rows and columns). Entries should be center aligned unless left aligning them would make them easier to read (longer entries, usually). Word entries in the body should use sentence case. Leave cells blank if the element is not applicable or if data were not obtained; use a dash in cells and a general note if it is necessary to explain why cells are blank.   In reporting the data, consistency is key: Numerals should be expressed to a consistent number of decimal places that is determined by the precision of measurement. Never change the unit of measurement or the number of decimal places in the same column.

There are three types of notes for tables: general, specific, and probability notes. All of them must be placed below the table in that order.

General  notes explain, qualify or provide information about the table as a whole. Put explanations of abbreviations, symbols, etc. here.

Example:  Note . The racial categories used by the US Census (African-American, Asian American, Latinos/-as, Native-American, and Pacific Islander) have been collapsed into the category “non-White.” E = excludes respondents who self-identified as “White” and at least one other “non-White” race.

Specific  notes explain, qualify or provide information about a particular column, row, or individual entry. To indicate specific notes, use superscript lowercase letters (e.g.  a ,  b ,  c ), and order the superscripts from left to right, top to bottom. Each table’s first footnote must be the superscript  a .

a  n = 823.  b  One participant in this group was diagnosed with schizophrenia during the survey.

Probability  notes provide the reader with the results of the tests for statistical significance. Asterisks indicate the values for which the null hypothesis is rejected, with the probability ( p value) specified in the probability note. Such notes are required only when relevant to the data in the table. Consistently use the same number of asterisks for a given alpha level throughout your paper.

* p < .05. ** p < .01. *** p < .001

If you need to distinguish between two-tailed and one-tailed tests in the same table, use asterisks for two-tailed p values and an alternate symbol (such as daggers) for one-tailed p values.

* p < .05, two-tailed. ** p < .01, two-tailed. † p <.05, one-tailed. †† p < .01, one-tailed.

Borders 

Tables should only include borders and lines that are needed for clarity (i.e., between elements of a decked head, above column spanners, separating total rows, etc.). Do not use vertical borders, and do not use borders around each cell. Spacing and strict alignment is typically enough to clarify relationships between elements.

Example of a table in the text of an APA 7 paper. Note the lack of vertical borders.

Tables from Other Sources

If using tables from an external source, copy the structure of the original exactly, and cite the source in accordance with  APA style .

Table Checklist

(Taken from the  Publication Manual of the American Psychological Association , 7th ed., Section 7.20)

• Is the table necessary?
• Does it belong in the print and electronic versions of the article, or can it go in an online supplemental file?
• Are all comparable tables presented consistently?
• Are all tables numbered with Arabic numerals in the order they are mentioned in the text? Is the table number bold and left-aligned?
• Are all tables referred to in the text?
• Is the title brief but explanatory? Is it presented in italicized title case and left-aligned?
• Does every column have a column heading? Are column headings centered?
• Are all abbreviations; special use of italics, parentheses, and dashes; and special symbols explained?
• Are the notes organized according to the convention of general, specific, probability?
• Are table borders correctly used (top and bottom of table, beneath column headings, above table spanners)?
• Does the table use correct line spacing (double for the table number, title, and notes; single, one and a half, or double for the body)?
• Are entries in the left column left-aligned beneath the centered stub heading? Are all other column headings and cell entries centered?
• Are confidence intervals reported for all major point estimates?
• Are all probability level values correctly identified, and are asterisks attached to the appropriate table entries? Is a probability level assigned the same number of asterisks in all the tables in the same document?
• If the table or its data are from another source, is the source properly cited? Is permission necessary to reproduce the table?

Figures include all graphical displays of information that are not tables. Common types include graphs, charts, drawings, maps, plots, and photos. Just like tables, figures should supplement the text and should be both understandable on their own and referenced fully in the text. This section details elements of formatting writers must use when including a figure in an APA document, gives an example of a figure formatted in APA style, and includes a checklist for formatting figures.

Preparing Figures

In preparing figures, communication and readability must be the ultimate criteria. Avoid the temptation to use the special effects available in most advanced software packages. While three-dimensional effects, shading, and layered text may look interesting to the author, overuse, inconsistent use, and misuse may distort the data, and distract or even annoy readers. Design properly done is inconspicuous, almost invisible, because it supports communication. Design improperly, or amateurishly, done draws the reader’s attention from the data, and makes him or her question the author’s credibility. Line drawings are usually a good option for readability and simplicity; for photographs, high contrast between background and focal point is important, as well as cropping out extraneous detail to help the reader focus on the important aspects of the photo.

Parts of a Figure

All figures that are part of the main text require a number using Arabic numerals (Figure 1, Figure 2, etc.). Numbers are assigned based on the order in which figures appear in the text and are bolded and left aligned.

Under the number, write the title of the figure in italicized title case. The title should be brief, clear, and explanatory, and both the title and number should be double spaced.

The image of the figure is the body, and it is positioned underneath the number and title. The image should be legible in both size and resolution; fonts should be sans serif, consistently sized, and between 8-14 pt. Title case should be used for axis labels and other headings; descriptions within figures should be in sentence case. Shading and color should be limited for clarity; use patterns along with color and check contrast between colors with free online checkers to ensure all users (people with color vision deficiencies or readers printing in grayscale, for instance) can access the content. Gridlines and 3-D effects should be avoided unless they are necessary for clarity or essential content information.

Legends, or keys, explain symbols, styles, patterns, shading, or colors in the image. Words in the legend should be in title case; legends should go within or underneath the image rather than to the side. Not all figures will require a legend.

Notes clarify the content of the figure; like tables, notes can be general, specific, or probability. General notes explain units of measurement, symbols, and abbreviations, or provide citation information. Specific notes identify specific elements using superscripts; probability notes explain statistical significance of certain values.

A generic example of a figure formatted in APA 7 style.

Figure Checklist 

(Taken from the  Publication Manual of the American Psychological Association , 7 th ed., Section 7.35)

• Is the figure necessary?
• Does the figure belong in the print and electronic versions of the article, or is it supplemental?
• Is the figure simple, clean, and free of extraneous detail?
• Is the figure title descriptive of the content of the figure? Is it written in italic title case and left aligned?
• Are all elements of the figure clearly labeled?
• Are the magnitude, scale, and direction of grid elements clearly labeled?
• Are parallel figures or equally important figures prepared according to the same scale?
• Are the figures numbered consecutively with Arabic numerals? Is the figure number bold and left aligned?
• Has the figure been formatted properly? Is the font sans serif in the image portion of the figure and between sizes 8 and 14?
• Are all abbreviations and special symbols explained?
• If the figure has a legend, does it appear within or below the image? Are the legend’s words written in title case?
• Are the figure notes in general, specific, and probability order? Are they double-spaced, left aligned, and in the same font as the paper?
• Are all figures mentioned in the text?
• Has written permission for print and electronic reuse been obtained? Is proper credit given in the figure caption?
• Have all substantive modifications to photographic images been disclosed?
• Are the figures being submitted in a file format acceptable to the publisher?
• Have the files been produced at a sufficiently high resolution to allow for accurate reproduction?

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• Knowledge Base
• APA Style 7th edition
• How to format tables and figures in APA Style

APA Format for Tables and Figures | Annotated Examples

Published on November 5, 2020 by Jack Caulfield . Revised on January 17, 2024.

A table concisely presents information (often numbers) in rows and columns. A figure is any other image or illustration you include in your text—anything from a bar chart to a photograph.

Tables and figures differ in terms of how they convey information, but APA Style presents them in a similar format—preceded by a number and title, and followed by explanatory notes (if necessary).

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Table of contents

Apa table format, apa figure format, numbering and titling tables and figures, formatting table and figure notes, where to place tables and figures, referring to tables and figures in the text, frequently asked questions about apa tables and figures.

Tables will vary in size and structure depending on the data you’re presenting, but APA gives some general guidelines for their design. To correctly format an APA table, follow these rules:

• Table number in bold above the table.
• Brief title, in italics and title case, below the table number.
• No vertical lines.
• Horizontal lines only where necessary for clarity.
• Clear, concise labels for column and row headings.
• Numbers consistently formatted (e.g. with the same number of decimal places).
• Any relevant notes below the table.

An example of a table formatted according to APA guidelines is shown below.

The table above uses only four lines: Those at the top and bottom, and those separating the main data from the column heads and the totals.

Create your tables using the tools built into your word processor. In Word, you can use the “ Insert table ” tool.

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Any images used within your text are called figures. Figures include data visualization graphics—e.g. graphs, diagrams, flowcharts—as well as things like photographs and artworks.

To correctly format an APA figure, follow these rules:

• Figure number in bold above the figure.
• Brief title, in italics and title case, under the figure number.
• If necessary, clear labels and legends integrated into the image.
• Any relevant notes below the figure.

An example of a figure formatted according to APA guidelines is shown below.

Keep the design of figures as simple as possible. Use colors only where necessary, not just to make the image look more appealing.

For text within the image itself, APA recommends using a sans serif font (e.g. Arial) with a size between 8 and 14 points.

For other figures, such as photographs, you won’t need a legend; the figure consists simply of the image itself, reproduced at an appropriate size and resolution.

Each table or figure is preceded by a number and title.

Tables and figures are each numbered separately, in the order they are referred to in your text. For example, the first table you refer to is Table 1; the fourth figure you refer to is Figure 4.

The title should clearly and straightforwardly describe the content of the table or figure. Omit articles to keep it concise.

The table or figure number appears on its own line, in bold, followed by the title on the following line, in italics and title case.

Where a table or figure needs further explanation, notes should be included immediately after it. These are not your analysis of the data presented; save that for the main text.

There are three kinds of notes: general , specific , and probability . Each type of note appears in a new paragraph, but multiple notes of the same kind all appear in one paragraph.

Only include the notes that are needed to understand the table or figure. It may be that it is clear in itself, and has no notes, or only probability notes; be as concise as possible.

General notes

General notes come first. They are preceded by the word “ Note ” in italics, followed by a period. They include any explanations that apply to the table or figure as a whole and a citation if it was adapted from another source, and they end with definitions of any abbreviations used.

Specific notes

Specific notes refer to specific points in the table or figure. Superscript letters (a, b, c …) appear at the relevant points in the table or figure and at the start of each note to indicate what they refer to. They are used when it’s necessary to comment on a specific data point or term.

Probability notes

Probability notes give p -values for the data in the table or figure. They correspond to asterisks (and/or other symbols) in the table or figure.

You have two options for the placement of tables and figures in APA Style:

• Option 1: Place tables and figures throughout your text, shortly after the parts of the text that refer to them.
• Option 2: Place them all together at the end of your text (after the reference list) to avoid breaking up the text.

If you place them throughout the text, note that each table or figure should only appear once. If you refer to the same table or figure more than once, don’t reproduce it each time—just place it after the paragraph in which it’s first discussed.

Align the table or figure with the text along the left margin. Leave a line break before and after the table or figure to clearly distinguish it from the main text, and place it on a new page if necessary to avoid splitting it across multiple pages.

If you place all your tables and figures at the end, you should have one table or figure on each page. Begin with all your tables, then place all your figures afterwards.

Avoid making redundant statements about your tables and figures in your text. When you write about data from tables and figures, it should be to highlight or analyze a particular data point or trend, not simply to restate what is already clearly shown in the table or figure:

• As Table 1 shows, there are 115 boys in Grade 4, 130 in Grade 5, and 117 in Grade 6 …
• Table 1 indicates a notable preponderance of boys in Grade 5. It is important to take this into account because …

Additionally, even if you have embedded your tables and figures in your text, refer to them by their numbers, not by their position relative to the text or by description:

• The table below shows…
• Table 1 shows…
• As can be seen in the image on page 4…
• As can be seen in Figure 3…
• The photograph of a bald eagle is an example of…
• Figure 1 is an example of…

In an APA Style paper , use a table or figure when it’s a clearer way to present important data than describing it in your main text. This is often the case when you need to communicate a large amount of information.

Before including a table or figure in your text, always reflect on whether it’s useful to your readers’ understanding:

• Could this information be quickly summarized in the text instead?
• Is it important to your arguments?
• Does the table or figure require too much explanation to be efficient?

If the data you need to present only contains a few relevant numbers, try summarizing it in the text (potentially including full data in an appendix ). If describing the data makes your text overly long and difficult to read, a table or figure may be the best option.

APA doesn’t require you to include a list of tables or a list of figures . However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures.

A list of tables and list of figures appear (in that order) after your table of contents , and are presented in a similar way.

If you adapt or reproduce a table or figure from another source, you should include that source in your APA reference list . You should also acknowledge the original source in the note or caption for the table or figure.

Tables and figures you created yourself, based on your own data, are not included in the reference list.

In most styles, the title page is used purely to provide information and doesn’t include any images. Ask your supervisor if you are allowed to include an image on the title page before doing so. If you do decide to include one, make sure to check whether you need permission from the creator of the image.

Include a note directly beneath the image acknowledging where it comes from, beginning with the word “ Note .” (italicized and followed by a period). Include a citation and copyright attribution . Don’t title, number, or label the image as a figure , since it doesn’t appear in your main text.

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Figures and Charts

What this handout is about.

This handout will describe how to use figures and tables to present complicated information in a way that is accessible and understandable to your reader.

Do I need a figure/table?

When planning your writing, it is important to consider the best way to communicate information to your audience, especially if you plan to use data in the form of numbers, words, or images that will help you construct and support your argument.  Generally speaking, data summaries may take the form of text, tables or figures. Most writers are familiar with textual data summaries and this is often the best way to communicate simple results. A good rule of thumb is to see if you can present your results clearly in a sentence or two. If so, a table or figure is probably unnecessary. If your data are too numerous or complicated to be described adequately in this amount of space, figures and tables can be effective ways of conveying lots of information without cluttering up your text. Additionally, they serve as quick references for your reader and can reveal trends, patterns, or relationships that might otherwise be difficult to grasp.

So what’s the difference between a table and a figure anyway?

Tables present lists of numbers or text in columns and can be used to synthesize existing literature, to explain variables, or to present the wording of survey questions. They are also used to make a paper or article more readable by removing numeric or listed data from the text. Tables are typically used to present raw data, not when you want to show a relationship between variables.

Figures are visual presentations of results. They come in the form of graphs, charts, drawings, photos, or maps.  Figures provide visual impact and can effectively communicate your primary finding. Traditionally, they are used to display trends and patterns of relationship, but they can also be used to communicate processes or display complicated data simply.  Figures should not duplicate the same information found in tables and vice versa.

Using tables

Tables are easily constructed using your word processor’s table function or a spread sheet program such as Excel. Elements of a table include the Legend or Title, Column Titles, and the Table Body (quantitative or qualitative data). They may also include subheadings and footnotes. Remember that it is just as important to think about the organization of tables as it is to think about the organization of paragraphs. A well-organized table allows readers to grasp the meaning of the data presented with ease, while a disorganized one will leave the reader confused about the data itself, or the significance of the data.

Title: Tables are headed by a number followed by a clear, descriptive title or caption. Conventions regarding title length and content vary by discipline. In the hard sciences, a lengthy explanation of table contents may be acceptable. In other disciplines, titles should be descriptive but short, and any explanation or interpretation of data should take place in the text. Be sure to look up examples from published papers within your discipline that you can use as a model. It may also help to think of the title as the “topic sentence” of the table—it tells the reader what the table is about and how it’s organized. Tables are read from the top down, so titles go above the body of the table and are left-justified.

Column titles: The goal of column headings is to simplify and clarify the table, allowing the reader to understand the components of the table quickly. Therefore, column titles should be brief and descriptive and should include units of analysis.

Table body: This is where your data are located, whether they are numerical or textual. Again, organize your table in a way that helps the reader understand the significance of the data. Be sure to think about what you want your readers to compare, and put that information in the column (up and down) rather than in the row (across). In other words, construct your table so that like elements read down, not across. When using numerical data with decimals, make sure that the decimal points line up. Whole numbers should line up on the right.

Other table elements

Tables should be labeled with a number preceding the table title; tables and figures are labeled independently of one another. Tables should also have lines demarcating different parts of the table (title, column headers, data, and footnotes if present). Gridlines or boxes should not be included in printed versions. Tables may or may not include other elements, such as subheadings or footnotes.

Quick reference for tables

Tables should be:

• Centered on the page.
• Numbered in the order they appear in the text.
• Referenced in the order they appear in the text.
• Labeled with the table number and descriptive title above the table.
• Labeled with column and/or row labels that describe the data, including units of measurement.
• Set apart from the text itself; text does not flow around the table.

Table 1. Physical characteristics of the Doctor in the new series of Doctor Who

Table 2. Physical characteristics of the Doctor in the new series of Doctor Who

Using figures

Figures can take many forms. They may be graphs, diagrams, photos, drawings, or maps. Think deliberately about your purpose and use common sense to choose the most effective figure for communicating the main point. If you want your reader to understand spatial relationships, a map or photograph may be the best choice. If you want to illustrate proportions, experiment with a pie chart or bar graph. If you want to illustrate the relationship between two variables, try a line graph or a scatterplot (more on various types of graphs below). Although there are many types of figures, like tables, they share some typical features: captions, the image itself, and any necessary contextual information (which will vary depending on the type of figure you use).

Figure captions

Figures should be labeled with a number followed by a descriptive caption or title. Captions should be concise but comprehensive. They should describe the data shown, draw attention to important features contained within the figure, and may sometimes also include interpretations of the data. Figures are typically read from the bottom up, so captions go below the figure and are left-justified.

The most important consideration for figures is simplicity. Choose images the viewer can grasp and interpret clearly and quickly. Consider size, resolution, color, and prominence of important features. Figures should be large enough and of sufficient resolution for the viewer to make out details without straining their eyes. Also consider the format your paper will ultimately take. Journals typically publish figures in black and white, so any information coded by color will be lost to the reader.  On the other hand, color might be a good choice for papers published to the web or for PowerPoint presentations. In any case, use figure elements like color, line, and pattern for effect, not for flash.

Additional information

Figures should be labeled with a number preceding the table title; tables and figures are numbered independently of one another. Also be sure to include any additional contextual information your viewer needs to understand the figure. For graphs, this may include labels, a legend explaining symbols, and vertical or horizontal tick marks. For maps, you’ll need to include a scale and north arrow. If you’re unsure about contextual information, check out several types of figures that are commonly used in your discipline.

Quick reference for figures

Figures should be:

• Labeled (under the figure) with the figure number and appropriate descriptive title (“Figure” can be spelled out [“Figure 1.”] or abbreviated [“Fig. 1.”] as long as you are consistent).
• Referenced in the order they appear in the text (i.e. Figure 1 is referenced in the text before Figure 2 and so forth).
• Set apart from the text; text should not flow around figures.

Every graph is a figure but not every figure is a graph. Graphs are a particular set of figures that display quantitative relationships between variables. Some of the most common graphs include bar charts, frequency histograms, pie charts, scatter plots, and line graphs, each of which displays trends or relationships within and among datasets in a different way. You’ll need to carefully choose the best graph for your data and the relationship that you want to show. More details about some common graph types are provided below. Some good advice regarding the construction of graphs is to keep it simple. Remember that the main objective of your graph is communication. If your viewer is unable to visually decode your graph, then you have failed to communicate the information contained within it.

Pie charts are used to show relative proportions, specifically the relationship of a number of parts to the whole. Use pie charts only when the parts of the pie are mutually exclusive categories and the sum of parts adds up to a meaningful whole (100% of something). Pie charts are good at showing “big picture” relationships (i.e. some categories make up “a lot” or “a little” of the whole thing). However, if you want your reader to discern fine distinctions within your data, the pie chart is not for you. Humans are not very good at making comparisons based on angles. We are much better at comparing length, so try a bar chart as an alternative way to show relative proportions. Additionally, pie charts with lots of little slices or slices of very different sizes are difficult to read, so limit yours to 5-7 categories.

The chart shows the relative proportion of fifteen elements in Martian soil, listed in order from “most” to “least”: oxygen, silicon, iron, magnesium, calcium, sulfur, aluminum, sodium, potassium, chlorine, helium, nitrogen, phosphorus, beryllium, and other. Oxygen makes up about ⅓ of the composition, while silicon and iron together make up about ¼. The remaining slices make up smaller proportions, but the percentages aren’t listed in the key and are difficult to estimate. It is also hard to distinguish fifteen colors when comparing the pie chart to the color coded key.

The chart shows the relative proportion of five leisure activities of Venusian teenagers (tanning, trips to Mars, reading, messing with satellites, and stealing Earth cable). Although each of the five slices are about the same size (roughly 20% of the total), the percentage of Venusian teenagers engaging in each activity varies widely (tanning: 80%, trips to Mars: 40%, reading: 12%, messing with satellites: 30%, stealing Earth cable: 77%). Therefore, there is a mismatch between the labels and the actual proportion represented by each activity (in other words, if reading represents 12% of the total, its slice should take up 12% of the pie chart area), which makes the representation inaccurate. In addition, the labels for the five slices add up to 239% (rather than 100%), which makes it impossible to accurately represent this dataset using a pie chart.

Bar graphs are also used to display proportions. In particular, they are useful for showing the relationship between independent and dependent variables, where the independent variables are discrete (often nominal) categories. Some examples are occupation, gender, and species. Bar graphs can be vertical or horizontal. In a vertical bar graph the independent variable is shown on the x axis (left to right) and the dependent variable on the y axis (up and down). In a horizontal one, the dependent variable will be shown on the horizontal (x) axis, the independent on the vertical (y) axis. The scale and origin of the graph should be meaningful. If the dependent (numeric) variable has a natural zero point, it is commonly used as a point of origin for the bar chart. However, zero is not always the best choice. You should experiment with both origin and scale to best show the relevant trends in your data without misleading the viewer in terms of the strength or extent of those trends.

The graph shows the number of male and female spaceship crew members for five different popular television series: Star Trek (1965), Battlestar (1978), Star Trek: TNG (1987), Stargate SG-1 (1997), and Firefly (2002). Because the television series are arranged chronologically on the x-axis, the graph can also be used to look for trends in these numbers over time.

Although the number of crew members for each show is similar (ranging from 9 to 11), the proportion of female and male crew members varies. Star Trek has half as many female crew members as male crew members (3 and 6, respectively), Battlestar has fewer than one-fourth as many female crew members as male crew members (2 and 9, respectively), Star Trek: TNG has four female crew members and six male crew members, Stargate SG-1 has less than one-half as many female crew members as male crew members (3 and 7, respectively), and Firefly has four female and five male crew members.

Frequency histograms/distributions

Frequency histograms are a special type of bar graph that show the relationship between independent and dependent variables, where the independent variable is continuous, rather than discrete. This means that each bar represents a range of values, rather than a single observation. The dependent variables in a histogram are always numeric, but may be absolute (counts) or relative (percentages). Frequency histograms are good for describing populations—examples include the distribution of exam scores for students in a class or the age distribution of the people living in Chapel Hill. You can experiment with bar ranges (also known as “bins”) to achieve the best level of detail, but each range or bin should be of uniform width and clearly labeled.

XY scatter plots

Scatter plots are another way to illustrate the relationship between two variables. In this case, data are displayed as points in an x,y coordinate system, where each point represents one observation along two axes of variation. Often, scatter plots are used to illustrate correlation between two variables—as one variable increases, the other increases (positive correlation) or decreases (negative correlation). However, correlation does not necessarily imply that changes in one variable cause changes in the other. For instance, a third, unplotted variable may be causing both. In other words, scatter plots can be used to graph one independent and one dependent variable, or they can be used to plot two independent variables. In cases where one variable is dependent on another (for example, height depends partly on age), plot the independent variable on the horizontal (x) axis, and the dependent variable on the vertical (y) axis. In addition to correlation (a linear relationship), scatter plots can be used to plot non-linear relationships between variables.

The scatter plot shows the relationship between temperature (x-axis, independent variable) and the number of UFO sightings (y-axis, dependent variable) for 53 separate data points. The temperature ranges from about 0°F and 120°F, and the number of UFO sightings ranges from 1 to 10. The plot shows a low number of UFO sightings (ranging from 1 to 4) at temperatures below 80°F and a much wider range of the number of sightings (from 1 to 10) at temperatures above 80°F. It appears that the number of sightings tends to increase as temperature increases, though there are many cases where only a few sightings occur at high temperatures.

XY line graphs

Line graphs are similar to scatter plots in that they display data along two axes of variation. Line graphs, however, plot a series of related values that depict a change in one variable as a function of another, for example, world population (dependent) over time (independent). Individual data points are joined by a line, drawing the viewer’s attention to local change between adjacent points, as well as to larger trends in the data. Line graphs are similar to bar graphs, but are better at showing the rate of change between two points. Line graphs can also be used to compare multiple dependent variables by plotting multiple lines on the same graph.

Example of an XY line graph:

The line graph shows the age (in years) of the actor of each Doctor Who regeneration for the first through the eleventh regeneration. The ages range from a maximum of about 55 in the first regeneration to a minimum of about 25 in the eleventh regeneration. There is a downward trend in the age of the actors over the course of the eleven regenerations.

General tips for graphs

Strive for simplicity. Your data will be complex. Don’t be tempted to convey the complexity of your data in graphical form. Your job (and the job of your graph) is to communicate the most important thing about the data. Think of graphs like you think of paragraphs—if you have several important things to say about your data, make several graphs, each of which highlights one important point you want to make.

Strive for clarity. Make sure that your data are portrayed in a way that is visually clear. Make sure that you have explained the elements of the graph clearly. Consider your audience. Will your reader be familiar with the type of figure you are using (such as a boxplot)? If not, or if you’re not sure, you may need to explain boxplot conventions in the text. Avoid “chartjunk.” Superfluous elements just make graphs visually confusing. Your reader does not want to spend 15 minutes figuring out the point of your graph.

Strive for accuracy. Carefully check your graph for errors. Even a simple graphical error can change the meaning and interpretation of the data. Use graphs responsibly. Don’t manipulate the data so that it looks like it’s saying something it’s not—savvy viewers will see through this ruse, and you will come off as incompetent at best and dishonest at worst.

How should tables and figures interact with text?

Placement of figures and tables within the text is discipline-specific. In manuscripts (such as lab reports and drafts) it is conventional to put tables and figures on separate pages from the text, as near as possible to the place where you first refer to it. You can also put all the figures and tables at the end of the paper to avoid breaking up the text. Figures and tables may also be embedded in the text, as long as the text itself isn’t broken up into small chunks. Complex raw data is conventionally presented in an appendix. Be sure to check on conventions for the placement of figures and tables in your discipline.

You can use text to guide the reader in interpreting the information included in a figure, table, or graph—tell the reader what the figure or table conveys and why it was important to include it.

When referring to tables and graphs from within the text, you can use:

• Clauses beginning with “as”: “As shown in Table 1, …”
• Passive voice: “Results are shown in Table 1.”
• Active voice (if appropriate for your discipline): “Table 1 shows that …”
• Parentheses: “Each sample tested positive for three nutrients (Table 1).”

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.

Bates College. 2012. “ Almost everything you wanted to know about making tables and figures.” How to Write a Paper in Scientific Journal Style and Format , January 11, 2012. http://abacus.bates.edu/~ganderso/biology/resources/writing/HTWtablefigs.html.

Cleveland, William S. 1994. The Elements of Graphing Data , 2nd ed. Summit, NJ: Hobart Press..

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

University of Chicago Press. 2017. The Chicago Manual of Style , 17th ed. Chicago & London: University of Chicago Press.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Home » Figures in Research Paper – Examples and Guide

Figures in Research Paper – Examples and Guide

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Figures in Research Paper

Figures play an essential role in research papers as they provide a visual representation of data, results, and concepts presented in the text. Figures can include graphs, charts, diagrams, photographs, and other visual aids that enhance the reader’s understanding of the research.

Importance of Figures in Research Paper

Here are some specific ways in which figures can be important in a research paper:

• Visual representation of data : Figures can be used to present data in a clear and concise way. This makes it easier for readers to understand the results of experiments and studies.
• Simplify complex ideas: Some concepts can be difficult to explain using words alone. Figures can be used to simplify complex ideas and make them more accessible to a wider audience.
• Increase reader engagement : Figures can make a research paper more engaging and interesting to read. They break up long blocks of text and can make the paper more visually appealing.
• Support arguments: Figures can be used to support arguments made in the paper. For example, a graph or chart can be used to show a correlation between two variables, providing evidence for a particular hypothesis.
• Convey important information: Figures can be used to convey important information quickly and efficiently. This is particularly useful when the paper is being read by someone who is short on time and needs to quickly understand the main points.

Types of Figures in Research Paper

There are several types of figures commonly used in research papers, including:

• Line graphs: These are used to show trends or changes in data over time.
• Bar graphs: These are used to compare data across different categories or groups.
• Pie charts: These are used to show proportions or percentages of data.
• Scatterplots : These are used to show the relationship between two variables.
• Tables : These are used to present large amounts of data in a structured format.
• Photographs or images : These are used to provide visual context or examples of the research being presented.
• Diagrams or schematics : These are used to illustrate complex processes or systems.

How to add Figures to Research Paper

Adding figures to a research paper can be a great way to visually convey important information to the reader. Here are some general guidelines for adding figures to your research paper:

• Determine the appropriate type of figure: Depending on the information you want to convey, you may want to use a graph, chart, table, photograph, or other type of figure.
• Label the figure: Give your figure a descriptive title and number it. Also, include a brief caption that explains what the figure shows.
• Place the figure in the appropriate location : Generally, figures should be placed as close as possible to the text that refers to them. For example, if you mention a figure in the middle of a paragraph, it should be placed within that paragraph.
• Format the figure appropriately: Ensure that the figure is clear and easy to read. Use consistent fonts and font sizes, and make sure the figure is large enough to be easily seen.
• Cite the source of the figure: If the figure was not created by you, you must cite the source of the figure in your paper. This includes citing the author or creator, the date of creation, and any relevant publication information.
• Consider copyright : Ensure that you have permission to use any figures that are copyrighted. If the figure is copyrighted, you may need to obtain permission from the copyright holder to use it in your paper.

How to Label Figures in Research Paper

Labeling figures in a research paper is an important task that helps readers to understand the content of the paper. Here are the steps to label figures in a research paper:

• Decide on the numbering system: Before labeling the figures, decide on the numbering system that you want to use. Typically, figures are numbered consecutively throughout the paper, with the first figure being labeled as “Figure 1,” the second figure as “Figure 2,” and so on.
• Choose a clear and concise caption: A caption is a brief description of the figure that appears below the figure. It should be clear and concise and should describe the content of the figure accurately. The caption should be written in a way that readers can understand the figure without having to read the entire paper.
• Place the label and caption appropriately: The label and caption should be placed below the figure. The label should be centered and should include the figure number and a brief title. The caption should be placed below the label and should describe the figure in detail.
• Use consistent formatting: Make sure that the formatting of the labels and captions is consistent throughout the paper. Use the same font, size, and style for all figures in the paper.
• Reference figures in the text : When referring to a figure in the text, use the figure number and label. For example, “As shown in Figure 1, the results indicate that…”

Figure 1. Distribution of survey responses

In this example, “Figure 1” is the figure number, and “Distribution of survey responses” is a brief title or description of the figure.

The label should be placed at the top of the figure and should be centered. It should be clear and easy to read. It’s important to use a consistent format for all figures in the paper to make it easier for readers to follow.

Examples of Figures in Research Paper

Examples of Figures in Research Papers or Thesis are as follows:

Line graphs Example

Bar graphs Example

Pie charts Example

Scatterplots Example

Tables Example

Photographs or images Example

Diagrams or schematics Example

Purpose of Figures in Research Paper

Some common purposes of figures in research papers are:

• To summarize data: Figures can be used to present data in a concise and easy-to-understand manner. For example, graphs can be used to show trends or patterns in data, while tables can be used to summarize numerical information.
• To support arguments : Figures can be used to support arguments made in the text of the research paper. For example, a figure showing the results of an experiment can help to demonstrate the validity of the conclusions drawn from the experiment.
• To illustrate concepts: Figures can be used to illustrate abstract or complex concepts that are difficult to explain in words. For example, diagrams or illustrations can be used to show the structure of a complex molecule or the workings of a machine.
• To enhance readability: Figures can make a research paper more engaging and easier to read. By breaking up long blocks of text, figures can help to make the paper more visually appealing and easier to understand.
• To provide context : Figures can be used to provide context for the research being presented. For example, a map or diagram can help to show the location or layout of a study site or experimental setup.
• To compare results : Figures can be used to compare results from different experiments or studies. This can help to highlight similarities or differences in the data and draw comparisons between different research findings.
• To show relationships : Figures can be used to show relationships between different variables or factors. For example, a scatter plot can be used to show the correlation between two variables, while a network diagram can be used to show how different elements are connected to each other.
• To present raw data: Figures can be used to present raw data in a way that is easier to understand. For example, a heat map can be used to show the distribution of data over a geographic region, while a histogram can be used to show the distribution of data within a single variable.

Advantages of Figures in Research Paper

Figures (such as charts, graphs, diagrams, and photographs) are an important component of research papers and offer several advantages, including:

• Enhancing clarity : Figures can help to visually communicate complex data or information in a clear and concise manner. They can help readers better understand the research and its findings.
• Saving space : Figures can often convey information more efficiently than text, allowing researchers to present more information in less space.
• Improving readability : Figures can break up large blocks of text and make a paper more visually appealing and easier to read.
• Supporting arguments: Figures can be used to support arguments made in the text and help to strengthen the overall message of the paper.
• Enabling comparisons: Figures can be used to compare different data points, which can be difficult to do with text alone. This can help readers to see patterns and relationships in the data more easily.
• Providing context : Figures can provide context for the research, such as showing the geographic location of study sites or providing a visual representation of the study population.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Maximizing the Impact of Your Research Paper with Graphs and Charts

The value of visual aids in today’s data-driven study environment cannot be overlooked.

Graphs and charts are effective communication tools that enable academics to convey difficult information to their audience. These visual tools, which range from pie charts to bar graphs, can significantly improve the readability and impact of research articles.

Graphs and charts are indispensable in contemporary research, whether they are used to compare data points, depict trends and patterns, or just break up text-heavy parts.

In this article, the significance of graphs and charts in research papers will be examined, along with their benefits, types of visual aids that are frequently employed, recommended practices for their use, and typical pitfalls to avoid.

By the end of this article, you will have a comprehensive understanding of the role of graphs and charts in research, and how to use them effectively in your next paper.

If you are not well versed with charts and graphs there is a quick fix. Join online c ourses on Data visualization . This will help you learn tricks involved in representing the data in a quick way. If you are still not comfortable the hire a research consultant who will help you in representing the data in a most adorable way. I have written an article on Why Hiring a Research Consultant Can Benefit Your PhD Work? . Please refer the article for further details.

Why add Graphs and Charts to my research paper?

How graphs and charts in research papers are critical, enhance visual appeal and readability of data, convey complex information effectively, enable easy comparison of data points, facilitate understanding of trends and patterns, improved data visualization, enhanced readability, better communication of results, increased credibility, better understanding of data, choosing the right type of graph or chart, making sure the graph or chart is accurate, using clear and concise labelling, adding a title and caption, formatting the graph or chart appropriately, line graphs, scatter plots, best software options for drawing charts and graphs, how do i choose the appropriate scale for my charts and graphs, how do i handle missing data when creating charts and graphs, how to handle huge data sets using charts and graphs, when should i use logarithmic scales in my charts and graphs, how do i ensure that my charts and graphs are accessible to all audiences, including those with disabilities, whether charts and graphs come under copyright protection, what are some common mistakes to avoid when using charts and graphs in research papers, how many graphs and charts should be there in a research paper, what should be the size of graphs and charts in a research paper, can i place charts and graphs at the end of paper instead of in between text, can i place charts and graphs at the end of text as single column instead of two column text, introduction.

Graphs and charts are often used in the Results section of a research paper to visually represent data and findings obtained from experiments or analyses. They may also be included in the Discussion section to support or refute the hypotheses or research questions presented in the Introduction section.

In the Results section, graphs and charts may be used to display statistical analyses such as histograms, scatter plots, and box plots. They can also be used to show trends over time or across different groups, such as line graphs or bar charts. Tables may also be used to present numerical data in a more organized and concise manner.

I have written an article on How to write Results Section of your Research Paper . The article helps you to represent the results in a better fashion, which will in turn increase the chances of paper acceptance.

In the Discussion section, graphs and charts may be used to support the interpretation of the results and to draw conclusions. They may also be used to compare the findings of the current study to previous research or to provide visual examples of the phenomena being studied.

I have written an article on 07 Easy Steps for Writing Discussion Section of a Research Paper . This article will help you in analyzing the charts and graphs to gain better insights.

It is important to note that while graphs and charts can be useful tools in a research paper, they should be used sparingly and only when they add value to the presentation of the data. Too many or poorly designed graphs can make the paper difficult to read and understand.

In research papers, graphs and charts are used to aid in the audience’s comprehension of the material being given. Graphs and charts give the data a visual representation that is simple to comprehend, evaluate, and compare.

Researchers may successfully communicate difficult information using graphs and charts, which increases the impact and accessibility of their findings.

Data from the study are best presented using graphs and charts. They can be used to draw attention to significant patterns and trends in the data, to present information in a comprehensible manner, and to engage viewers.

Graphs and charts can assist you in clearly expressing your ideas and leaving an impact, whether you are summarising data for a research paper or presenting study findings to a big audience.

Advantages of Using Graphs and Charts in Research Papers

The use of graphs and charts in research papers offers many advantages that cannot be achieved through text alone. The following points clearly elaborate on the same.

Long passages of text can be broken up using graphs and charts, which also offer a more understandable visual depiction of the data. Additionally, they can improve the research paper’s aesthetic attractiveness, which will draw readers in and keep them reading.

When given in the form of text or raw statistics, data sets can frequently be convoluted and challenging to comprehend. This information can be made more understandable and easier to interpret for the reader by using graphs and charts. Additionally, they can be used to contrast several data sets, which makes it simpler to spot connections and trends.

Graphs and charts allow researchers to present data in a way that makes it easy to compare different data points. For example, a bar graph can be used to compare the values of different categories, while a line graph can be used to track changes over time.

Data trends and patterns that might not be immediately obvious through text alone might be found using graphs and charts. A histogram, for instance, can be used to see the distribution of data points while a scatter plot can be used to find correlations between two variables. Researchers can more easily make sense of their data by using graphs and charts to better comprehend the underlying patterns and trends.

The Benefits of Using Graphs and Charts in Research Papers

There are many benefits to using graphs and charts in research papers, including:

Graphs and charts can help researchers effectively visualize their data, making it easier for them to see patterns, trends, and relationships within their data. This can help researchers make more informed decisions and draw more accurate conclusions based on their data.

Graphs and charts can make research papers more visually appealing and easier to read. By breaking up long blocks of text, graphs and charts can help to hold the reader’s attention and make the information more engaging.

Graphs and charts can help researchers effectively communicate their results to a variety of audiences. By using visual aids, researchers can effectively convey complex data and ideas in a simple, straightforward manner.

The use of graphs and charts can help to increase the credibility of a research paper. By effectively visualizing their data, researchers can demonstrate that their findings are based on a strong understanding of the data and that their results are robust and reliable.

Graphs and charts can help researchers to better understand their data. By visualizing the data, researchers can identify patterns, relationships, and trends that might not be immediately apparent in raw data or text-based summaries.

By taking advantage of the benefits of using graphs and charts in research papers, researchers can enhance the quality and impact of their research and effectively communicate their findings to a variety of audiences.

Best Practices for Using Graphs and Charts in Research Papers

There are several best practices that researchers should follow when using graphs and charts in their research papers. These include:

It is important to choose the right type of graph or chart to effectively convey the data and results. Researchers should consider the type of data they are working with, the relationships they want to highlight, and the message they want to convey when selecting a graph or chart.

It is important to ensure that the data represented in a graph or chart is accurate and that the graph or chart is properly labelled. Researchers should also be careful to ensure that the scale used in a graph or chart is appropriate for the data being displayed.

Labels should be clear, concise, and accurately describe the data being displayed. Researchers should use labelling to highlight the key points of their data and to make it easy for the reader to understand the message being conveyed.

A title and caption should be included with each graph or chart to provide context and to summarize the key findings. The title should accurately describe the graph or chart, while the caption should provide additional information and context.

The graph or chart should be presented in a clear, uncomplicated, and readable way. In addition to making sure the graph or chart has the right size and placement within the study report, researchers should avoid utilising too many colours or patterns.

Researchers can efficiently utilise graphs and charts to increase the visual appeal and readability of their research papers as well as to properly communicate their data and results by adhering to certain best practises.

Types of Graphs and Charts Commonly used in Research Papers

There are many types of graphs and charts that can be used in research papers, each with their own strengths and uses.

Bar graphs are used to compare the values of different categories or groups. They are best used to display data that is numerical in nature and can be represented in a structured, organized format. Bar graphs can be horizontal or vertical, and can be used to display data in a variety of ways, including grouped bar graphs, stacked bar graphs, and side-by-side bar graphs.

Line graphs are used to track changes over time and to display trends. They consist of a series of points connected by a line and can be used to display data in a variety of ways, including simple line graphs, multiple line graphs, and cumulative line graphs.

Pie charts are used to represent data as a proportion of the whole. They are best used to display data that is categorical in nature and to display the relationships between different categories.

Scatter plots are used to display the relationship between two variables. They consist of a series of points plotted on a set of axes, and can be used to identify correlations between the two variables.

Histograms are used to display the distribution of data. They consist of a series of bars that represent the frequency of data points within a specific range. Histograms are best used to display data that is numerical in nature and to display the distribution of data points over time.

By understanding the different types of graphs and charts, researchers can choose the best visual aid to convey their data and results effectively.

There are several popular software tools for creating graphs and charts for your research paper. These tools are widely used in academia and industry for visualizing data in a visually appealing and professional manner. Here are some of the best software options:

• Microsoft Excel : Excel is a widely used spreadsheet software that comes with a robust charting feature. It allows you to create a wide variety of charts, such as bar charts, line charts, scatter plots, and more. Excel also offers customization options for colors, fonts, and styles to create visually appealing charts.
• MATLAB : MATLAB is a popular software tool used in various fields of research, including engineering, physics, and finance. It has powerful graphing capabilities, with a wide range of plotting functions and customization options. MATLAB also provides advanced data analysis and visualization features, making it suitable for complex research papers.
• R : R is a popular open-source programming language and environment for statistical computing and graphics. It offers extensive libraries for data visualization, such as ggplot2, lattice, and base graphics, which provide a wide range of charting options for creating publication-quality graphs and charts.
• Tableau : Tableau is a powerful data visualization software that provides a user-friendly interface for creating interactive and visually appealing charts and dashboards. It offers a wide range of chart types and customization options, and allows you to connect to various data sources for easy data integration and visualization.
• Adobe Illustrator : Adobe Illustrator is a vector graphics software that provides advanced drawing and design tools for creating high-quality, professional-looking graphs and charts. It offers extensive customization options for colors, fonts, styles, and shapes, allowing you to create visually stunning graphics for your research paper.
• Google Charts : Google Charts is a free web-based tool that allows you to create interactive charts and graphs. It provides a wide range of chart types, such as bar charts, line charts, pie charts, and more, with easy-to-use customization options. Google Charts also offers integration with other Google products, such as Google Sheets, making it convenient for data visualization.

Here’s a comparison of the software tools for drawing graphs and charts:

Note: The cost of these software tools may vary based on different licensing options, usage plans, and academic discounts that may be available.

It’s important to consider factors such as features, customization options, data integration capabilities, interactivity, and cost when choosing the best software for your specific research paper. Depending on your requirements and preferences, you may find one of these software tools more suitable for your needs.

These are some of the best software options for creating graphs and charts for your research paper. Choose the one that best suits your needs and familiarity with the software, and ensure that the resulting graphs and charts are visually appealing and effectively communicate your research findings.

Key factors to consider when choosing the appropriate scale for your charts and graphs, with examples and visual aids:

• Data range: Your chart or graph’s scale should correspond to the range of values in your data. For instance, a bar chart with a scale that only goes up to 1,000 will not accurately depict the full range of the data if the data extends from 0 to 100,000. In this situation, a bigger scale that can hold the entire range of values could be preferable.
• Purpose of the chart or graph: Think about the goal of your graph or chart. Use a smaller scale that zooms in on a specific area of the data if you want to draw attention to a particular trend or pattern. You could wish to zoom in on a certain time period to draw attention to a certain pattern, for instance, if your line chart of temperature trends over time shows trends over time.
• Audience: Consider the audience that your graph or chart is intended to serve. Your data visualisation may need to be more or less explicit and detailed depending on who it is intended for. If you are presenting your study to a general audience, for instance, you might want to use a straightforward bar chart, however, if you are presenting to a more technical audience, you might want to use a more intricate line chart that provides more detail.
• Data distribution: Take your data’s distribution into account. You might want to choose a different scale if your data is skewed or contains outliers in order to better depict the data. For instance, you might wish to use a logarithmic scale if your data are skewed to the right in order to more accurately depict the distribution of the data.

By considering these factors, you can choose an appropriate scale that effectively communicates the data in your chart or graph and enhances the readability and credibility of your research paper.

Handling missing data in charts and graphs can be challenging, but there are several strategies you can use to minimize its impact on the representation of your data:

• Use visual cues: When you have missing data points, you can use visual cues such as dots or a different colour or pattern to indicate the missing information. This helps the reader understand that the data is missing and avoids misleading them with false information.
• Interpolate: In some cases, you may be able to estimate the missing data by interpolating values between two known data points. This can be useful for creating a continuous line chart or graph, but it should be clearly labelled as estimated data.
• Use statistical methods: Statistical methods, such as imputation, can be used to fill in missing data based on patterns in the existing data. This should be done carefully and with caution, as it can introduce bias into the data if not done correctly.
• Leave it out: If the amount of missing data is significant, it may be best to simply exclude it from your charts and graphs. This will avoid giving false impressions of trends or patterns in the data.
• Provide a separate graph or chart: If the missing data is important, you can provide a separate chart or graph that specifically shows the missing data. This allows the reader to see the complete picture, and understand the limitations of the data you are presenting.

When handling missing data, it’s important to be transparent about the methods you used and to clearly label any estimated or imputed data. This will help to ensure the accuracy and reliability of your research paper, and to build trust with your readers.

Handling huge data in charts can be a challenge, but there are several strategies that can help make the data more manageable and easier to understand. Here are some tips for handling huge data in charts:

• Use aggregated data: Aggregating data into categories or grouping similar data points can help reduce the amount of data being displayed and make it easier to understand.
• Filter data: Filtering data to only display relevant information can also help reduce the amount of data in a chart.
• Use multiple charts: If the data is too large to be displayed effectively in a single chart, consider using multiple charts to break down the data into smaller, more manageable parts.
• Use dynamic charts: Dynamic charts, such as interactive line charts or bar charts, allow users to select and view specific data points, making it easier to understand large amounts of data.
• Use colour coding: Color coding data points in a chart can help distinguish between different data sets and make it easier to see trends or patterns.
• Use a smaller time scale: If the data is time-based, consider using a smaller time scale, such as days or weeks instead of months or years, to reduce the amount of data in a chart.
• Use data visualizations: Data visualizations, such as heat maps or treemaps, can help represent large amounts of data in a more manageable and easy-to-understand format.
• Use summary statistics: Summary statistics, such as mean, median, or mode, can help simplify the data and make it easier to understand.
• Use simplifying shapes: Using simplifying shapes, such as circles or squares, can help represent large amounts of data in a way that is easy to understand.
• Consider a combination of methods: Using a combination of the methods above can help effectively handle huge data in charts and make it easier for audiences to understand.

By using these strategies, you can effectively handle huge data in charts and ensure that your data is represented in a clear and concise manner.

A logarithmic scale is a type of scale used in charts and graphs to represent a large range of values in a compact and readable manner. Unlike a linear scale, which represents equal increments of a variable with equal distances, a logarithmic scale represents equal increments of the variable as equal percentages.

The logarithmic scale is particularly useful when dealing with data sets that have an extensive range of values. For example, if a data set has values that range from 1 to 1,000,000, a linear scale would require a very long axis to accommodate all of the values, making it difficult to read and understand. On a logarithmic scale, the axis would be compressed, making it easier to see the trends and patterns in the data.

In research papers, the use of a logarithmic scale can be particularly helpful when dealing with data sets that have a skewed distribution, such as data that has a few extremely large values and many smaller values. By using a logarithmic scale, researchers can better represent the distribution of the data and highlight the trends and patterns that may not be apparent on a linear scale.

It’s important to note that when using a logarithmic scale, the values on the axis are logarithms, not actual values. This means that the increments on the axis represent multiplicative factors, not additive factors. When interpreting a chart with a logarithmic scale, it’s important to consider the scale and understand that the values are represented differently than on a linear scale.

In conclusion, the use of a logarithmic scale can be a powerful tool for researchers when dealing with data sets that have a large range of values. By compressing the axis and representing equal increments of the variable as equal percentages, logarithmic scales can help make data easier to understand and highlight important trends and patterns.

Let’s consider the number of confirmed COVID-19 cases in a country for 10 days. Here is a table representing the data:

As you can see, the logarithmic scale makes it easier to see the relative changes in the number of cases, especially as the values get larger. On a logarithmic scale, equal increments of the number of cases represent equal percentages, rather than equal distances. This allows you to see changes that might not be as noticeable on a linear scale.

To calculate the values for the logarithmic scale, you would take the logarithm (base 10) of each value in the data. Here is an example of how to calculate the logarithm of the value for the 5th day (800 cases):

code log10(800) = 2.903

This means that on a logarithmic scale, the value for the 5th day would be represented as 2.903.

To ensure that your charts and graphs are accessible to all audiences, including those with disabilities, consider the following:

• Use clear and simple language: Use plain language and avoid technical terms when labelling your charts and graphs, to make it easier for everyone to understand the data.
• Provide alternative text: Provide alternative text descriptions for images, including charts and graphs, so that screen readers can describe the content to users with visual impairments.
• Use accessible colours: Avoid using colour as the only means of conveying information, and ensure that the colour contrast between the text and background is high enough to be easily readable by people with colour vision deficiencies.
• Use clear and concise labels: Label the axes and data points clearly and concisely, and include units of measurement where appropriate.
• Use accessible file formats: Save charts and graphs in accessible file formats, such as PDF or SVG, which can be easily read by assistive technology.
• Consider touch and keyboard navigation: Make sure that your charts and graphs are usable for people who navigate the web using touch or keyboard controls, by ensuring that all interactive elements can be operated using keyboard commands.
• Test for accessibility: Test your charts and graphs with assistive technology, such as screen readers, to ensure that they are fully accessible to all users.

By following these guidelines, you can ensure that your charts and graphs are accessible to everyone, regardless of their abilities. This will help to increase the reach and impact of your research paper, and promote greater inclusivity in the scientific community.

It is easier for readers to comprehend complex material when it is presented visually through charts and graphs. It’s crucial to think about whether the charts and graphs you create for a research paper are subject to copyright laws and whether you require permission to use them.

Original works of authorship, such as literary, musical, theatrical, and aesthetic works, are protected by copyright law. If they are made by a person or group and have enough creative expression, charts and graphs might be regarded as original works of authorship.

Research articles frequently utilise charts and graphs that are based on publicly accessible data, such as statistics from the government or data from surveys. 

These kinds of information are typically regarded as being in the public domain and can be utilised without a licence.

Charts and graphs produced by an individual or group, however, and containing a considerable amount of original creative work may be protected by copyright legislation. 

In certain situations, you might need to ask the copyright holder for permission before using the graph or chart in your research report.

When using charts and graphs in a research paper, it’s important to consider the source of the data and whether the chart or graph is protected by copyright law. If you are unsure, it’s always best to err on the side of caution and to obtain permission from the copyright owner before using the chart or graph in your research paper.

When using charts and graphs in research papers, it’s important to avoid common mistakes that can undermine the effectiveness of your data visualization. Here are some common mistakes to watch out for:

• Overcomplicating the visualization: Avoid using too many colours, patterns, or elements in your chart or graph, as this can make it difficult for the reader to understand the data. Stick to simple, clean designs that emphasize the data.
• Ignoring the scale: Be careful when choosing the scale for your chart or graph, as the wrong scale can distort the data and give a false impression of the data.
• Improper labelling: Make sure to label the axes of your chart or graph clearly and accurately, and include units of measurement where appropriate.
• Not using appropriate chart or graph types: Choosing the right chart or graph type is important for effectively communicating the data. For example, if you have categorical data, use a bar chart, not a line chart.
• Ignoring the data distribution: Consider the distribution of your data, and adjust the scale and chart type accordingly. For example, if your data is skewed, you may want to use a logarithmic scale to better represent the data.
• Overloading the chart or graph: Avoid putting too much data into a single chart or graph, as this can make it difficult for the reader to understand the data. Instead, break the data down into multiple charts or graphs as needed.
• Using outdated or irrelevant data: Make sure to use the most up-to-date and relevant data in your charts and graphs, as outdated or irrelevant data can undermine the credibility of your research paper.

By avoiding these common mistakes, you can ensure that your charts and graphs effectively communicate the data.

In conclusion, charts and graphs play a crucial role in visualizing and communicating data in research papers. The use of charts and graphs allows researchers to convey information effectively and efficiently, helping the reader to understand complex data easily. Whether it’s a bar graph, scatter plot, heatmap, or histogram, each type of chart has its unique strengths and weaknesses.

Choosing the right type of chart and using it effectively is crucial to getting your message across in a research paper. Additionally, using a logarithmic scale and ensuring accessibility to all audiences can make your charts and graphs more effective and user-friendly. To make the most of charts and graphs in research, it is important to keep in mind the guidelines, best practices, and common mistakes to avoid.

Frequently Asked Questions

The number of graphs and charts in a research paper can vary depending on the nature of the research, the specific requirements of the paper, and the preferences of the author or the guidelines of the target journal or conference. There is no fixed rule or standard for the exact number of graphs and charts in a research paper. However, it is generally recommended to use graphs and charts judiciously, ensuring that they are relevant, clear, and effectively convey the research findings.

The size of graphs and charts in a research paper should be chosen carefully to ensure that they are clear, readable, and effectively convey the information to the readers. Here are some general guidelines for the size of graphs and charts in a research paper: Legibility: The graphs and charts should be large enough to be easily read and interpreted by the readers, even when printed or displayed at a reduced size. The font size of labels, legends, and annotations should be legible, typically ranging from 10-12 points, depending on the font type. Proportionality: The size of the graphs and charts should be proportional to the available space in the paper and the content being presented. Avoid using excessively small graphs or charts that may be difficult to understand or interpret. Clarity: The graphs and charts should be clear and not overly cluttered. Use appropriate line thicknesses, marker sizes, and bar widths that are visually clear and distinguishable. Avoid overcrowding the graphs or charts with too much information, which may make them difficult to read or interpret. Journal/Conference Guidelines: Follow the guidelines of the target journal or conference for the size of graphs and charts. Some journals or conferences may have specific requirements or recommendations for the size of visuals in research papers. Consistency: Ensure that the size of graphs and charts is consistent throughout the paper. Use a consistent style for fonts, colors, and other graphical elements to maintain a cohesive visual appearance. Accessibility: Consider accessibility requirements, such as ensuring that the size of graphs and charts is suitable for readers with visual impairments. Providing alternative text descriptions for visuals can also enhance accessibility.

Yes, it is common practice in research papers to place charts and graphs at the end of the paper as appendices or as separate sections, especially if they are large or numerous. This can help improve the flow and readability of the main text, as readers can refer to the visuals in the appendices or separate sections as needed without interrupting their reading of the main content.

Yes, you can place charts and graphs at the end of a research paper as single-column visuals, even if the main text is formatted in two columns. However, it’s important to ensure that the placement of visuals at the end of the paper does not disrupt the overall organization and readability of your research paper.

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Ultimate Guide on Creating Comprehensive Graphs for Your Research Paper

If you have two minutes to skim through a research paper, what would you go through? Probably the introduction, the conclusion, and? The graphs? That’s right! Graphs are the best way to visually illustrate your research paper. Research papers usually have massive amounts of data and complicated concepts to explain. And, graphs can be used […]

If you have two minutes to skim through a research paper, what would you go through? Probably the introduction, the conclusion, and? The graphs? That’s right!

Graphs are the best way to visually illustrate your research paper. Research papers usually have massive amounts of data and complicated concepts to explain.

And, graphs can be used to represent these data and concepts in a visual, easy to understand manner. Graphs can effectively help to deliver the message that you want to convey.

Also, adding graphs to your research paper can make it much, much more interesting. Something that might be needed in an otherwise monotonous research paper.

Apart from visually representing your data, graphs can also give a concrete angle to the idea of your hypothesis and research paper.

But, simply adding graphs for the sake of it won’t do. Graphs are meant to make your thesis sound more interesting and explain things better. But, you can easily go wrong with it by adding graphs that do not necessarily complement your research paper.

A good graph can make the world of difference to your research paper. It can make the text of your research paper sound more self-explanatory. If you are a student, then this means you’ll get better grades for your research paper.

So, in this ultimate guide, let’s look at some super-helpful tricks and tips on adding comprehensive graphs to your research paper to make them more interesting and appealing.

Know Your Audience

Knowing your primary audience is important to understand before you decide on the types of graphs that you want to add. 

Not everyone understands graphs the same way. So, ensure that you understand your audience first before proceeding with the addition of graphs to your research paper.

Think about who is going to read your research paper. Is it a scientist, preschool teacher, or your neighbor who works in a finance firm? Different types of graphs would be suitable for people with different levels of understanding.

Based on the capacity of your audience and how they will perceive your research paper, you can decide on the types of graphs that best suit them. Here’s a list to help you out:

If your audience is less experienced, then you should go with graphs that are easier to understand without any extensive knowledge about graphs. Here are some such types of graphs:

• Linear graph
• Multi-set bar graph

If your audience is well versed with the basics of your research paper’s topic and is from your industry, then you can go with more advanced types of graphs. Here are some advanced types of graphs which you can use for a more experienced audience:

• Stacked bar graph
• Stacked area graph
• Spiral plot
• Point and figure chart
• Choropleth map
• Candlestick chart

Imagine if you were to go for a Choropleth map for an inexperienced audience for your research paper. It would be a total disaster! Your message would not be delivered as efficiently. 

Similarly, a simple linear graph might seem amateur in a research paper meant for scientists, when the concept could have been explained with the help of a more advanced graph.

Hence, knowing your audience is very important to understand while you write your research paper and create comprehensive graphs for it.

Keep a Check on the Aesthetics

While creating and adding graphs to your research paper, it is also important to think about its aesthetics too. There is no point in adding a graph if it looks messy and unclear. Right from the colors, the fonts, to the placement of your graphs, everything counts.

The use of the right colors can completely transform your graphs and your research paper. Whereas if you add colors that look off-putting, then your audience might not be able to read and understand your graphs well. They might even put down your research paper right away. 

Colors have the ability to enhance your graphs and improve their readability. For instance, if you use different colors to represent different data points, then your graph will instantly look more readable for your audience.

The contrast of colors is also an essential aspect to consider. You should avoid using dark backgrounds with lighter colored fonts and plots. As this will decrease the readability.

As a general rule, have a lighter background and contrasting colored elements. For example, if you use a white background for your graph, do not plot your graphs with yellow-colored lines as these will not be distinguishable. Instead, use darker colored lines.

Fonts of your graphs are also a very crucial element. If you use fonts that are too large, then your graph might look messy.

While, if you use fonts that are too small, then your graph might not be readable. Readers might have to strain their eyes to understand your graph. Hence, use the right size for the fonts in your graphs.

Also, try not to choose fancy fonts that are not easily understandable. Go with the standard serif fonts. You should also format your fonts properly. For example, use bold and italic fonts wherever highlighting is necessary. Do not bold the entire text. Use it selectively.

Icons can be a great addition to your research paper’s graphs. They can make your research paper self explanatory. You can use icons to label charts or graphs. Or you can also use them to label different elements of your graphs.

While using icons, you should, again, think about the color contrast. Your icons should look clear and distinguishable in the background. For example, use a darker color icon on a lighter colored background.

The fonts inside your icons also matter. Whether you design your own fonts, or you use make my graph tools, you must ensure that the fonts inside icons (if any) are readable without having to strain the eyes.

Make Your Readers Visualize Effectively

The point of adding any graph, chart, or illustration to your research paper is to help your readers easily understand your point.

Reading and understanding research papers cannot be everyone’s cup of tea. Hence, you should make persistent efforts to make it as easy-to-understand as possible.

Your audience will be able to best understand your graphs only when they can visualize them effectively. Visualization is easy to say, but difficult to implement.

You need to ensure that your graphs are designed in a way so that they can be visualized effectively. For this, you need to look at your graph with a fresh set of eyes.

If your graph seems a little too complicated, try to dial it down by breaking down a single graph into multiple smaller graphs. Or, you can also combine two or more smaller graphs to represent everything on a single graph, if that seems like a better representation.

Try to understand how your readers, who do not know entirely about your topic, look at the graphs. Will they be able to visualize and understand the message you are trying to convey?

If not, then recreate better graphs. If your graph looks plain, take the help of online make my graph tools that can aid you to create beautiful, comprehensive graphs at supper affordable rates.

If you nail this part, then your research paper will be a great resource for everyone to refer to. And, your graphs and visual representations will also be widely shared in your industry.

Know What You Want to Convey

The message you want to deliver or the concept you want to explain to your readers with the help of graphs is also important to consider. 

What exactly do you not want to convey? Do you want to add a visual representation of data? Do you want to create scientific infographics that easily explain your research paper’s findings? Do you want to visually explain the differences between the two sets of data?

Based on the message that you want to convey, you can create different types of graphs. Here are a few types of graphs that can help you get started:

Hierarchical

Any concept that forms a hierarchy can be easily represented using hierarchical graphs.

You can create beautiful graphs with hierarchical representations using an easy-to-use online graphic maker tool like MindTheGraph.

A histogram is a graph using which you can represent the frequency distribution of a set of continuous data. You can visualize the shape of the data points and their underlying distribution.

If your research paper consists of data specific to geographical locations, then you can represent that result with the help of geospatial data. Geospatial graphs represent geographical locations through latitudes, longitudes, or the names of geographic locations.

Multidimensional

Multidimensional graphs can be used to represent data that can be better visualized and represented in more than two dimensions. These can be very effective in helping your readers effectively visualize your data and findings.

You can easily create beautiful graphs in multidimensional using online infographic maker tools like Mind the Graph.

Here’s an example of a template that you can use for creating a multidimensional infographic for your research paper.

Temporal graphs can be used to represent data that usually change with time. You can plot different data points with one of the axes of your graph as the time axis.

Pie charts are a circular statistical graph that can be used to represent different proportions of data.

Scatter plots

Scatter plots can be used to explain the relationship between two sets of data in a visual format. In scatter plots, dots are used to represent different numerical values.

Timetable charts

Timetable charts are used to represent scientific data in the form of timelines.

Venn diagrams

Venn diagrams are one of the most commonly used formats for visual presentation. Venn diagrams are used to show all possible logical relations amongst a finite group of things. These can be great for representing the similarities and differences between two or more things.

Stacked area graphs

A stacked area chart or graph is an extension of an area chart. Here, several groups of data are represented in the graph by stacking them, one above the other.

Stream graphs

Stream graphs are another form of stacked area graphs. In a stream graph, instead of stacking the layers, one above the other, layers are positioned around a central axis.

Stacked bar graphs

Stacker bar graphs are similar to stacked graphs, except where the same concept is applied to bar graphs. Different groups of data are represented by stacking them in the same bar graph, one above the other.

Parallel sets

Parallel sets are used to represent the flow and proportions of data. These represent data frequencies instead of individual data points.

Multi-set bar charts

Multi-set bar charts, also known as clustered bar charts, are a type of bar chart. Here, two or more data sets are represented side by side for better understanding and interpretation. All the bar charts use a common axis that may be X-axis or Y-axis.

Ask Others to Share Their Feedback

Lastly, a new set of eyes to review and critique your research paper’s graphs is almost as crucial as the process of designing the graphs.

You would probably love and admire the graphs you have created. But others might have a completely different opinion about it. Hence, it is best to get others’ opinions on this.

The best way to go about it is to pick people who most likely fit your primary audience. For example, if your research paper is meant for readers experienced in your industry, then pick someone with the same kind of industry experience.

Ask them to review your graph, analyze their initial reaction, and gather their feedback. Are they able to understand your graphs? Is your graph readable and easy-to-digest without you having to explain it in depth?

Asking and answering these questions will help you understand the most likely reaction from your primary audience. 

If the reviewer finds it difficult to understand, you should consider simplifying our graphs. You can do this either by using a simpler type of graph or using multiple graphs in place of one.

Whereas, if the reviewer finds the graphs unnecessary or amateur, then you might consider using more advanced graphs or removing them altogether.

We can conclude by saying that graphs can make or break your research paper. People can perceive your research paper in a completely different light if you have added the right graphs to it.

Right from selecting the type of graphs, to the colors and fonts to use, everything must be carefully thought upon before you start creating graphs. 

Take your time and create good comprehensive graphs for your research paper. And, by doing that, you will find that people appreciate your work a lot more than they would otherwise.

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About Fabricio Pamplona

Fabricio Pamplona is the founder of Mind the Graph - a tool used by over 400K users in 60 countries. He has a Ph.D. and solid scientific background in Psychopharmacology and experience as a Guest Researcher at the Max Planck Institute of Psychiatry (Germany) and Researcher in D'Or Institute for Research and Education (IDOR, Brazil). Fabricio holds over 2500 citations in Google Scholar. He has 10 years of experience in small innovative businesses, with relevant experience in product design and innovation management. Connect with him on LinkedIn - Fabricio Pamplona .

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An Effective Guide to Explain Graphs in Thesis and Research Paper

10 Popular Online Tools for Representing Graphs

Table of contents

Effective guide to explaining graphs in thesis and research papers: tips and tools, 10 popular online tools for representing graphs:.

When explaining graphs in a thesis and research paper, it is essential to provide a clear and concise interpretation of the data represented in the graph. In this article, iLovePhD presented you with an effective guide to explain graphs in the thesis and research paper.

Title and Caption : Begin by providing a clear title for the graph that summarizes its main purpose or finding. Follow it with a descriptive caption that highlights the key elements and trends depicted in the graph. Make sure the caption provides sufficient context and explains any abbreviations or symbols used.

Introduce the graph : In the text preceding the graph, provide a brief introduction to the topic or research question being addressed. Explain why the graph is relevant and how it contributes to answering the research question or supporting the thesis. This helps readers understand the purpose of the graph before delving into its details.

Describe the axes and variables : Clearly identify and label the axes of the graph. Explain what each axis represents and the units of measurement involved. Additionally, define the variables or data points represented on the graph.

Data Points : Draw attention to significant data points or noteworthy features of the graph, such as peaks, troughs, or sudden changes. Describe these points in the context of the research question or thesis statement. Explain any anomalies or unexpected trends observed in the graph.

Highlight trends or patterns : Analyze the graph and identify any significant trends, patterns, or relationships that can be observed. Explain whether the data shows an increase, decrease, fluctuation, or any other notable pattern. Use comparative language (e.g., “higher than,” “lower than,” “increasing,” and “decreasing”) to highlight these patterns and their significance. Use specific data points or numerical values from the graph to support your analysis.

Statistical Analysis : If applicable, provide statistical analysis of the data presented in the graph. Mention the statistical methods used, such as means, standard deviations, or significance tests. This adds rigor to your explanation and reinforces the credibility of your findings.

Provide supporting evidence : Whenever possible, supplement your explanations with additional evidence or information from your research or other sources. This can help to validate the patterns or trends observed in the graph and strengthen your thesis argument.

Interpret the implications : Discuss the implications and significance of the observed trends or patterns. Explain why these findings are important and how they contribute to your overall thesis or research question. Connect the information presented in the graph to the broader context of your study.

Limitations and Uncertainties : Acknowledge any limitations or uncertainties associated with the graph or the data it represents. Discuss potential sources of error, sample size issues, or confounding factors that may have influenced the results. This demonstrates a thoughtful analysis and helps readers understand the scope and reliability of the findings.

Relate to other parts of your thesis : Consider how the graph aligns with other information or analyses presented in your thesis. Highlight any connections between the graph and previous findings, literature reviews, or theoretical frameworks. This will help to create a cohesive narrative and reinforce the validity of your conclusions.

Use clear and concise language : Write your explanations in a clear and concise manner, avoiding jargon or complex language whenever possible. Aim to make your interpretation accessible to readers who may not have a specialized background in your field.

Include captions and references : Make sure to include a caption for each graph that provides a clear title and describes its content. Additionally, provide appropriate citations or references for the graph , following the citation style guidelines specified by your institution or field of study.

The specific approach to explaining graphs may vary depending on your discipline and the nature of your research. It’s crucial to strike a balance between providing enough information to understand the graph and avoiding excessive detail. Keep your explanations concise and focused on the most relevant aspects of the graph.

When it comes to representing graphs in a thesis and research paper, there are several online tools available that can assist you in creating professional and visually appealing visualizations. Here are 10 popular online tools for representing graphs:

Plotly : Plotly provides a wide range of interactive and customizable graph types. It allows you to create visually stunning graphs with options for 2D and 3D re presentations , as well as animations.

Tableau Public : Tableau Public is a powerful data visualization tool that allows you to create interactive graphs and dashboards. You can easily connect your data and create professional-looking visualizations.

Microsoft Excel : Excel offers a range of graphing options and is widely used for data analysis and visualization. It provides a user-friendly interface for creating various types of charts, including bar graphs, line graphs, scatter plots, and more.

Google Charts : Google Charts is a free tool that enables you to create a wide variety of charts and graphs. It offers a simple and intuitive interface with options for customization and interactivity.

D3.js : D3.js is a JavaScript library that allows you to create dynamic and interactive data visualizations. It provides extensive flexibility and control over the design and behaviour of your graphs.

Infogram : Infogram is an easy-to-use tool that enables you to create infographics and data visualizations. It offers a range of graph types and templates to choose from, making it suitable for creating eye-catching visuals for your thesis.

Canva : Canva is a versatile design tool that includes graphing capabilities. It offers a wide range of templates and customization options, allowing you to create visually appealing graphs and charts .

Chart.js : Chart.js is a JavaScript library that provides a simple and responsive way to create static and interactive charts. It is lightweight and easy to implement, making it a popular choice for web-based visualizations.

Lucidchart : Lucidchart is a web-based diagramming tool that can be used for creating various types of graphs and flowcharts. It offers a drag-and-drop interface and collaboration features, making it suitable for complex visualizations.

Adobe Illustrator : Adobe Illustrator is professional design software that allows you to create vector-based graphics, including graphs and charts. It provides advanced customization options and is ideal for creating intricate and detailed visualizations.

These tools offer a range of options for creating graphs and visualizations, catering to different skill levels and design requirements. Choose the tool that best suits your needs and familiarity with the software to effectively represent graphs in your thesis.

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• Artificial intelligence

How to Create Precise Graphs, Diagrams or Images in a Research Paper

According to the American psychologist Howard Gardner, human intelligence can be divided into seven categories: visual-spatial, bodily kinesthetic, musical, interpersonal, intrapersonal, linguistic, and logical-mathematical. This implies our intelligence strengths can be different in each (so-called) intelligence profile and that everybody can be intelligent in many different ways.

Gardner says these differences “challenge an educational system that assumes that everyone can learn the same materials in the same way and that a uniform, universal measure suffices to test student learning.” The truth is that we learn and understand things differently, and these differences affect the manner we read academic papers. A research paper is usually a combination of written and visual information. We can assume that those who have a predominant linguistic intelligence would focus on written information, whereas those with a visual-spatial intelligence would feel more comfortable focusing on graphs, diagrams, or images. How to combine both to achieve a paper that engages readers with different intelligence profiles at par?

The Perfect Combination

The first thing we must understand is that, no matter how much visual support they have, papers are written works. Filling pages with unnecessary images, graphs, diagrams or any other kind of visual material is never a good idea. Remember that you are writing a professional academic paper and, therefore, your capacity to discern which material is important. Once this is clear, it is time to discern which information is likely to be visually demonstrated .

Some main ideas would help you to decide when to use graphs. Choose only information that can be clearer if explained visually, and only if it is so important that you desire the reader to keep focus on it more than in other parts. Besides, this piece of information must be qualitatively or quantitatively measurable.

Images can also be used to summarize; plenty of information can be perfectly summed up in a single graph. Lastly, another reason to use images is comparison. Graphs and diagrams are great tools to indicate the differences between two agents.

Do not fill up your images with too much information because it would complicate the readers’ understanding. Images combine or support the written words, but should not be used to replace them. A good combination of words and images can ease the paper’s general understanding.

Thinking Visually: How to Choose?

It is important to know the possibilities each tool offers. Graphs, for example, are good to express the mathematical relationship or statistical correlation between data. Line graphs are useful to present an evolution, circulant graphs are better to indicate proportional parts and column graphs are commonly used to compare different elements.

Researchers and academics are supposed to have a good command of graphs usage . However, the capacity of selecting which data is most likely to be shown this way makes the difference. Indeed, achieving a good command of these tools is quite difficult, but is possible with experience.

Last but not least, it is always helpful to consider the final goal of an academic paper: communication . Thus, if the graph clearly points to one of the research’s main statements, do not doubt in using it.

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Utilizing tables, figures, charts and graphs to enhance the readability of a research paper

Department of Pediatrics, College of Medicine and Health Sciences, National University of Science and Technology, Sohar, Sultanate of Oman

1 Department of Pediatrics, Seth G.S. Medical College and KEM Hospital, Mumbai, Maharashtra, India

Introduction

Every author aims to reach the maximum target audience through his/her research publication/s. Our previous editorials have touched upon the process of writing a quality research paper and its successful publication in an appropriate journal.[ 1 , 2 ] Journal-specific ”Instructions for Authors” generally have defined limits to the text and non-textual content for the benefit of space and presentation. Though the aim of a paper is to get its research point across through methodology, results, and discussion, readers often read the summary of data and analysis (only). Thus, the tables, figures, charts, and graphs are time and space-effective tools that not only help to understand the research presented in a simple manner but also engage and sustain the reader's interest.

Why use tables/figures/charts or graphs?

Reading text matter can often get monotonous – for the readers as well as the editors and reviewers. Using Tables/Figures/Charts or Graphs effectively provides a break from textual content monotony as well as provides an opportunity to process and connect information between text and images, promoting deeper learning. It is suggested that one non-textual element should be used for every 1000 words in a manuscript, which generally amounts to two for every three print pages.[ 3 ] The use of tables/figures/charts/graphs not only reduces the word count but also complements the text effectively. Although the text focuses on explaining findings, outlining trends, and providing contextual information, non-textual content allows readers to understand characteristics, distribution, and relationships between data, and visualize statistics/abstract concepts in a powerful manner. High-quality tables and figures also increase the likelihood of a manuscript being accepted for publication.[ 4 ] Note that the figures/artwork needs to be uploaded as separate files for most of the journals.

The CONSORT statement ( www.equator-ntework.org ) provides guidelines on how to report outcome-specific information in a published clinical trial report; however there are no definite recommendations on how to present non-textual elements, and this varies from one journal to another. Authors tend to prepare them based on their own understanding, often without much thought, and repeat the information presented in the main text. Moreover, while some journals have dedicated editors and resources to redraw or edit figures/tables, others simply publish whatever the authors submit. Thus, to improve the readability of the paper, it is primarily the author's responsibility to submit clear and useful tables, figures, charts, and graphs.

The heart of any research lies in its data, and most readers only get a glimpse of the data via the results. The closest one can get to raw statistics is through data presented in tables, figures, graphs, and supplementary material. Tables, figures, and graphs also help to classify and interpret data, highlight key findings, and present maximum data in a concise space. The author should make a deliberate decision on the presentation of his data early in the writing process. Using a sentence as text is more efficient while presenting up to half a dozen numbers in data or if the information can be summarized in three or lesser sentences.[ 5 ] Figures give an overall picture of concept (but without exact numerical data), while tables present exact values (but are less engaging and less interesting).[ 5 ] The final choice of the presentation depends on the type of data, statistical analysis, and relevant message to be delivered.[ 6 ]

General methodology of design and submission

The general structure followed by most non-textual elements is caption/legend/title, content, and footnotes. All data should be verified thoroughly for errors (especially outliers or unexpected spikes) and data sources should be cited in the footnotes/references. The presentation should be simple and clear enough for the reader to understand without any assumptions.[ 7 ] Each exhibit should be labeled clearly with a title and numbers (usually Arabic numerals) that are separate, unique, and consecutive based on their appearance in the text. The title should be self-explanatory and explain the information presented (what, where, and when) briefly. Footnotes should refer to restrictions, assumptions, abbreviations, explanatory notes, and unusual annotations. The formatting should be consistent throughout (across all tables/graphs) for easy comparison.[ 7 ] Design the figures, tables, and graphs to fit in one page on a scale that will be readable in print.[ 8 ] Always use the insert -> (arrow) page break function to ensure that each new Table/Figure/Graph is seen in the document on a new page. Data from the figures and tables should not be repeated in the text. Although tables/figures are often submitted separately or at the end of manuscript based on journal instructions, they should be referred to in the text at appropriate points by location statements i.e. Figures ​ Figures1 1 and ​ and2 2 or Tables ​ Tables1 1 and ​ and2 2 .[ 7 ] One should be careful during editing and proofreading, as contents and columns may get misplaced.[ 9 ] Ensure to follow the journal instructions regarding numbers and formats and glance through published examples in targeted journal. For additional data/tables/figures/graphs that do not fit into the journal's instructions or are still necessary to be displayed outside the word/Table limit, online appendages (or supplementary files) can be created. Do ask for feedback from experienced colleague/s (but not co-author) for the exhibit before final submissions.

A representative table already published in the JPGM earlier (reproduced from Shah S, Deshmukh CT, Tullu MS. The predictors of outcome and progression of pediatric sepsis and septic shock: A prospective observational study from western India. J Postgrad Med 2020;66:67-72 )

Representative figure/s already published in the JPGM earlier (reproduced from Mondkar SA, Tullu MS, Sathe P, Agrawal M. Lane-Hamilton syndrome – Is it really a needle in a haystack? J Postgrad Med 2022;68:162-7 )

Do’s and Don’ts while creating effective Tables.[ 8 , 9 , 12 , 14 , 15 ]

Types of graphical representations and their characteristics.[ 5 , 6 , 7 , 8 , 20 , 21 ]

Copyright issues

Material from government publications/public domain may be used without seeking permission; however, permission is required for all fully borrowed, adapted, or modified tables/figures/graphs not in the public domain, usually from the publishers, with appropriate credit notes in footnotes (as stated for the Journal of Postgraduate Medicine – JPGM).[ 9 , 10 ] All data sources should be identified for tables/figures created using information from other studies.[ 9 ] Authors should seek permissions from publishers early in their writing, as their research cannot be published until all written permissions have been submitted and approved.[ 9 ] It is good practice to maintain a copy of such permissions with the corresponding author in case a dispute arises later on.

Use of tables

Tables are meant to give a systematic overview of the results and provide a richer understanding/comprehension of study participant characteristics and principal research findings.[ 11 ] Since tables deal with larger groups of data, they are suitable when all data requires equal attention and readers can selectively scan the data of interest.[ 6 ] Tables can present precise numerical values and information with different units' side-by-side but may not analyze data trends.[ 6 ] However, due to the sheer amount of data, interpretation may take longer.[ 6 ]

Generally, the first table summarizes key characteristics of the study population allowing readers to assess the generalizability of the findings. Subsequent tables present details of associations/comparisons between variables, often crude findings followed by models adjusted for confounding factors.[ 11 ] Other tables include tables of lists, tables of inclusion/exclusion criteria for review, and summary of characteristics/results of study (systematic reviews) and characteristics of participants in narrative format (qualitative studies).[ 11 ]

A good table draws attention to the data and not the table itself; the reader should be able to express an opinion about results just by looking at it.[ 12 ] It should neither be too long nor wide; designing more rows than columns makes it easier to scan in portrait orientation.[ 9 , 11 ] JPGM guidelines permit a maximum of 10 columns and 25 rows in a table.[ 10 ] They are generally created from word documents as insert table and constructed before writing the content in text.[ 9 ] Most tables consist of five basic components: title, rows, columns, data fields, and footnotes. The title/legend should be concise but sufficiently informative.[ 13 ] The first column generally lists the independent variables in rows while subsequent columns present the dependent data. Column and row headings should include group sizes and measurement units (preferably an international system of units). Stubs (row headings) on the left side of a table describe row contents and should also list numerical definitions for the data i.e. the median ± SD (normal distribution), median with IQR (non-normally distributed data), or percentages (dichotomous data)[ 9 , 14 ] Use fewest decimal points necessary for accurate reporting of data.[ 14 ] Columns should present statistical analysis and significance ( P values) to highlight key findings.[ 14 ] Use well-labeled columns with the same format throughout (mean or percentiles).[ 3 ]

Each cell (data field) should contain only one numerical value and never be blank [use dash (-), ellipsis (…) or designate as “no data”]. Abbreviations should be limited; use abbreviations like “NA” very cautiously as it may be misinterpreted as not applicable/not available/not analyzed.[ 13 ] Combine tables when single variable is cross-tabulated or divide tables with too much of data.[ 7 ]

Footnotes should be brief, define abbreviations, statistical results ( P values and level of significance) and explain restrictions/discrepancies in the data. Footnotes should be ordered starting with the title of the table and working downwards from left to right. Symbols applying to the entire table should be in the title and those applying to the entire row/column should be after the row/column heading.[ 13 ] Most journals prefer superscripted letters instead of numbers. Symbols recommended by JPGM for footnotes (in order) are: *, †, ‡, §, ||, ¶, **, ††, ‡‡.[ 10 ]

Alignment and formatting: All text should be aligned to the left and numbers to the right.[ 7 ] Data fields with decimal points, hyphens/slashes, plus/minus symbols, or parentheses are aligned to these elements. For stubs continuing onto a second line, the corresponding data field should be aligned to the top line of the stub.[ 13 ] Tables can be made more meaningful, by converting data to ratios/percentages and sorting data as per the significance of variables, generally from left to right and top to bottom.[ 7 ] Data included in tables should conform with those in the main text, and percentages in rows and columns should sum up accurately.

Most journals have specific instructions for gridlines – only the top and bottom horizontal lines are used, with no vertical lines as columns are inherently aligned.[ 7 ] If tables are used from other publications, copyright permission should be obtained to reproduce them, and they should be appropriately referenced in the legend. There may be limitations as to the number of tables allowed depending on the Journal instructions and the type of article. Some Do's and Don'ts while creating tables are summarized in Table 1 .[ 8 , 9 , 12 , 14 , 15 ] Also, a representative table already published in the JPGM earlier has been reproduced herewith for better understanding [ Figure 1 ].

Use of figures

Figures are powerful communication tools that display patterns that are not visualized in the text or the tables. They can achieve a high educational impact by sustaining readers' interest and helping them understand trends, patterns, relationships among concepts and sequence of events.[ 3 ] Like tables, figures should be complete and self-explanatory. They should be designed thoughtfully, be relevant and be of good quality.[ 5 ] There may be limitations as to the number of figures allowed depending on the Journal instructions and type of the article. Figures can be statistical (graphs- as explained later) and non-statistical (clinical images, photographs, diagrams, illustrations and textual figures).[ 16 ] Non-statistical figures present visual information without data.[ 16 ] Clinical images and photographs [ultrasonograms, X-rays, computed tomography (CT) scans, magnetic resonance (MR) scans, images of patients, intraoperative photographs, tissue samples or microscopy findings] provide convincing and substantial information through illustrative examples from specific individuals and engage audiences, especially clinical professionals.[ 5 ] Illustrations help to explain structures, mechanisms, and relationships. Diagrams like “flowcharts”, “algorithms”, “pedigree charts”, and “maps” display complex relationships while “textual figures” describe steps of a procedure or summarize guidelines.

Structure: Figure legends (maximum of 40 words excluding credits) should be double-spaced and identified by consecutive Arabic numerals with the corresponding citation in the text. They reflect the data within, and consist of a brief title, experimental/statistical details, definitions of symbols/line or bar patterns and abbreviations/annotations.[ 15 ] Labels, numbers, and symbols should be clear, consistent, of uniform size and large enough to be legible after fitting figures to publication size.[ 15 ] Symbols, arrows, numbers, or letters used to identify parts of illustrations should be clearly identified, properly sized, placed, and explained in the legend. In case of photomicrographs, contrast the symbols/letters or arrows with background, and describe the internal scale (magnification) and method of staining.[ 10 ] If the figure has several parts (”collage”), they should be presented in order from left to right and top to bottom; this should be similarly followed for their description in the legend with labeling done as a, b, c, d, etc.[ 14 ]

Photos should have a minimum resolution of 300 dpi before digital manipulation, the acceptable formats for pictures/photos and figures in various journals being pdf, doc, ppt, jpg, gif, and tiff. Publication of color images may be chargeable which should be checked beforehand.[ 9 ] Often the print version of journal may present black and white images, with color images used in the online version.

Line diagrams: Black and white art with no shading often illustrates content better than a photograph, especially in the case of body anatomy or surgical techniques.[ 9 ] Their line weight should be consistent and not less than 0.25 pt. If scanned, they should be submitted as a tiff/jpeg image of at least 600 dpi and a width of 15 cm/6 inches.[ 14 ] Creating line diagrams may involve expensive professional help with issues of exclusive rights. Simple drawings can be scanned in a conventional office scanner at a minimum resolution of 600 dpi.[ 9 ] Drawings in shades of grey require a resolution of 1200 dpi or more, usually unavailable in regular office scanners.[ 9 ]

X-rays , which are photographic images, often lack good contrast, a problem magnified if the image must be enlarged. The quality of radiographs can be improved using Adobe Photoshop.[ 17 ] Figure captions in radiology should be utilized correctly and mention the modality, imaging plane and relevant technical information for images e.g. projection name on an x-ray, plane of a cross-sectional image, window setting of a CT section, and sequence name of an MR image.[ 17 ]

One may need to crop images to focus on the point of interest and maintain patient anonymity. Editing is usually done in tiff file format in software designed for image editing. Adjustments in brightness/contrast/color balance may help if raw image is not clear; however, it should not alter the meaning.[ 5 ] Colors should be easy to see (avoid yellow) and backgrounds should preferably be white. The tint should be no lower than 15%.[ 14 ] However, all digital modifications or enhancements of photographic images should be documented, step by step and the original raw files of unedited photographs/images should be available as supplementary files .[ 5 ]

Minimum resolution and design: Figures should be of high quality and resolution such that when final images are zoomed to 1600%, they should not blur or pixelate.[ 5 ] In case of reprints, care should be taken about picture quality.[ 3 ] JPGM requires a minimum resolution of 300 dpi or 1800 × 1600 pixels in TIFF format for digital images. Uploaded images should be within 4 MB in size and JPEG format. The JPGM also reserves the right to crop, rotate, reduce, or enlarge the photographs to an acceptable size.[ 10 ] One can use tools while creating figures and exporting data in another software; a few examples of open-source are Matplotlib (python plotting library), R, Inkscape, TikZ, PGF, GIMP, ImageMagick, D3 (Data-Driven-Documents), Cytoscape and Circos.[ 18 ]

Anonymity and Copyright: In the case of images, all unessential patient information or identifiers should be removed (masking or blurring only the eyes is no longer considered sufficient).[ 19 ] It is the author's responsibility to obtain written permission from the patient to use the photograph for educational purposes (whether the subject is identifiable or not) and archive it properly.[ 10 ] For images or descriptions that identify the patient, a statement about obtaining informed patient consent should be specified in the manuscript.[ 10 ] For figures published elsewhere, the original source should be acknowledged (via credit line in the figure legend) and the author should submit permission from copyright holder (usually the publisher) to reproduce the material before his/her manuscript is accepted.[ 3 , 19 ] Representative figure/s already published in the JPGM earlier have been reproduced herewith as an example [ Figure 2 ].

Use of graphs

Graphs allow the reader to visualize and compare data by highlighting patterns and relationships such as changes over time, frequency distribution, correlation, and relative share.[ 7 ] One should be precise with data values and presentation in graphs to avoid misinterpretation. Graphs can be created from data using the same software used for statistical analysis or by special programs. Depending on the results, data can be depicted in several different formats, such as line graphs, bar charts, data plots, maps, and pie charts.

What to use and when: The graphical format (bar graph, line graph, scatter lot, dot plot) can be decided based on the type of relationship to be shown. For example, line graphs demonstrate trends, bar graphs show magnitudes and pie charts show proportions.[ 9 , 16 ] The preferred graph also depends on the representative value of data – absolute value/fraction/average/median.[ 20 ] Graphs should accurately present findings, scale should start at zero and the axes should not be altered to make data meaningful.[ 15 ] Pie charts and 3D graphs are generally not recommended.[ 5 ] Table 2 summarizes different graphical formats with their brief description and uses.[ 5 , 6 , 7 , 8 , 20 , 21 ]

How to draw/construct: Most statistical programs create graphs with statistical computations. Special programs such as Prism and Sigmaplot can also be used.[ 14 ] Different formats can be visualized in the statistical program, and the one that best depicts the data can be chosen.[ 3 ] Actual numbers from which graphs are drawn should be provided.[ 10 ] Components of graphs include axes, labels, scales, tick/reference marks, symbols, and legends.[ 21 ] Independent variables are plotted on the horizontal axis while dependent variables on vertical axis.[ 4 ] Axis labels should be short, clear and indicate measurement variable/result, units, and number of group subjects (if any).[ 7 ] The axis scale should be proportional to data range so that visual data is not exaggerated/missed and minimum space is wasted.[ 20 ] Length of axes should be visually balanced (ratio of X to Y axis should be 1.0 to 1.3).[ 21 ] Provide explanations if the axis starts from non-zero values, is non-linear (logarithmic/exponential/rate) or scales before and after a break are different.[ 7 , 20 ] Symbols/lines/curves inside the two axes should be the most prominent features, wording in axes labels next prominent and axes and tick mark (outside of axes) least prominent.[ 21 ] Numbers and marks should be large enough to be legible even when compressed for print.[ 5 ] Symbols should be uniform and effectively used to designate important strata in figures. All graphs should be consistent in style and formatting. Footnotes should indicate P values (with appropriate statistical test) and discrepancies in data/items.[ 8 ]

A clear and concise legend (inside/outside) should describe the variables in the graph. It should also include values of lines, symbols and diagrams, abbreviations, acronyms as well as statistical tests, their levels of significance, sampling size, stains used for analysis, and magnification rate.[ 4 , 20 ] Annotations can highlight specific values/statistically significant differences in graphs.[ 20 ]

All unnecessary background lines (such as gridlines) are distracting and should be removed. The background should be the palest possible (preferably white) for the highest contrast and readability. Remove all default pre-styling formats and avoid 3D effects.[ 7 ] Data presentation can be intensified by eliminating clutter and refined in a vector graph editing program (without altering the position of marks representing data).[ 5 ] It is essential to minimize meaningless noise and maximize meaningful signals.[ 5 ]

Algorithms (combination of graph and table) are an excellent aid to demonstrate a decision tree. However, they can be difficult to construct due to decisions based on more than one variable. This presents clinical and technical difficulties in presenting all possible variations in a diagnosis or therapeutic decision.[ 9 ]

A representative graph and chart already published in the JPGM earlier has been reproduced herewith as an example [Figures ​ [Figures3 3 and ​ and4 4 ].

A representative graph already published in the JPGM earlier (reproduced from Bhatia S, Tullu MS, Kannan S, Gogtay NJ, Thatte UM, Lahiri KR. An unusual recurrence of antitubercular drug induced hepatotoxicity in a child. J Postgrad Med 2011;57:147-152 )

A representative chart already published in the JPGM earlier (reproduced from Agarwal S, Divecha C, Tullu MS, Deshmukh CT. A rare case of nephrotic syndrome: ‘Nailed’ the diagnosis. J Postgrad Med 2014;60:179-82 )

Use of supplementary materials

Supplementary materials refer to additional content (tables/graphs/appendices/videos/audios) that are not published in the main article. Scientific publications often come with strict word limits. Additional text or data which lengthens the print version can be accessed via digital supplementary files. Besides overcoming word restrictions, supplementary material provides additional information that is not essential in the main manuscript, but enhances understanding of research. They are available to interested readers to explore or replicate (methods/formulae/statistical models/algorithms/intervention pathways) the study for secondary research or teaching.[ 22 ] Thus, they serve as an online companion, complementing the main text. The most common supplementary files are tables and figures. Some instances of their use in various sections are as follows.[ 23 ]

In introduction: Table of summary of literature from various studies, detailed description of research topic, illustrations of concepts discussed, and glossaries of terms used.

In methodology: Participant details (sources, inclusion/exclusion lists, demography), instrumentation of constructs and variables, data collection techniques (survey questionnaires, participant forms), and data analysis techniques (coding sheets for content analysis, checklists) mathematical formulae used in calculations, data collection schedule.

In results and discussion: Additional results (often tables and figures), detailed analysis of limitations of the study or possible alternative explanations, programming code.

Other material includes references for supplementary files, translations, errata, audio, and video files.[ 23 ]

Examples of video/audio files include echocardiography recordings and ultrasound images. Specific information on the preparation of audio and video clips is available in the author guidelines. Video formats usually used are MPEG-4, QuickTime, or Windows media video. Audio supplements include WAV or MP3 format. Video size should be reduced to <10 MB and clips limited to 15–25 s. The resolution should be optimized by using video frame dimensions of 480 × 360 pixels and 640 × 480 pixels.[ 14 ]

However, supplemental material is available only in the online version- limiting immediate access to many readers.[ 5 ] Moreover, only readers with a strong interest in the research topic will access the online supplementary material.[ 5 ] The information in these files is often very extensive and not integrated with the main text appropriately, thus finding and extracting specific points from a supplement can be tedious.[ 24 ]

The utility of supplementary material varies as per the audience – additional tables and figures are more useful to readers, information about study protocol/data collection to peer reviewers, and completed checklists to journal editors. Due to the lack of guidance from journals (to both authors and reviewers) regarding its necessity or accuracy and due to the extensive nature of the files, supplementary material is rarely read/reviewed (though all the supplementary files are to be uploaded for peer-review with the main article files at the time of submission).[ 24 ] This increases the likelihood of missing errors in methods/analysis (submitted as supplementary files), thus placing the scientific accuracy and validity of the published research at risk.[ 24 ] Moreover, the availability of raw data to third parties via supplementary files raises concerns about security and data permanence.[ 22 ] The supplementary files often describe methods crucial to published research but are not included in references, thus many researchers remain uncited/unrecognized. Citations within supplementary material are also not appropriately tracked by citation indices. This can be overcome by direct hyperlinking sections of supplementary materials with the main manuscript.[ 24 ] Thus, supplementary data can be an asset if used thoughtfully; however, its indiscriminate use can hinder its actual purpose and be detrimental to the peer review process.

Concluding remarks

Tables, figures, graphs, and supplementary materials are vital tools which, when skillfully used, make complex data simple and clear to understand, within journal word restrictions. They engage and sustain interest and provide a brief visual summary narrative of study hypothesis- saving time and energy for readers, reviewers, and editors. They should be self-explanatory, complement the text and provide value to the paper. Producing clear, informative non-textual elements increases the chances of papers being published and read. Thus, the author should plan these elements early during the process of data collection/analysis and not as an afterthought. The author should have a good understanding of the types of data presentations and choose the simplest format that delivers his message best. They should be adapted to the journal's instructions to display and summarize essential content, without focusing too much on making it attractive or showcase one's technical expertise. Titles should be clear and simple, data should be consistent with results, and footnotes should be used effectively. Copyrights permissions, whenever necessary, should be obtained in advance and preserved appropriately.

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Erin Wright Writing

Writing-Related Software Tutorials

How to Write Figure Captions for Graphs, Charts, Photos, Drawings, and Maps

By Erin Wright

Figures are visuals such as charts, graphs, photos, drawings, and maps. Figures are normally identified by the capitalized word Figure and a number followed by a caption. A caption is a short block of text that gives information about the figure. The following seven tips explain how to write figure captions in your book, article, or research paper.

Although closely related, tables aren’t considered figures. See “ How to Write Table Titles ” for more information.

These tips are general guidelines based on our primary style guides . Each style guide has its own caption format (e.g., line spacing , margins, fonts). Therefore, you should consult your designated guide for specific recommendations, as necessary.

Seven Tips for Writing Figure Captions

Figure 1 and figure 2, located at the bottom of this post, demonstrate the guidelines explained in these tips.

1. Use captions instead of titles.

Figures in traditionally published books and scholarly writing usually have captions instead of titles. 2

However, some journals use titles and captions for figures. 3 Before submitting an article to a specific journal, always check its formatting requirements.

2. Place captions under figures.

Captions typically appear under figures. 4 Sometimes captions appear beside or even above figures; however, the decision to place captions in uncommon locations is normally made by the layout designer or production editor, not by the writer or copy editor. 5

Style Guide Alert: Written Music

The MLA Handbook (MLA style) and the Chicago Manual of Style (Chicago style) use the word Example rather than Figure to identify samples of written music in text. In addition, Chicago style places captions above written music instead of below, while MLA style keeps captions under written music. 6

Note that the academic version of Chicago style, Turabian, also recommends placing captions above written music but uses Figure instead of Example . 7

If you have music samples labeled as Example in addition to other figures, the music samples should be numbered separately from the figures (e.g., Example 1, Figure 1, Example 2, Figure 2).

3. Use a period after figure numbers.

Figures can be identified with regular numbers:

They can also be identified by double numbering in which the first number identifies the chapter and the second number identifies the figure:

Figure 7.10. (the tenth figure in chapter 7)

Figure 7.11. (the eleventh figure in chapter 7)

Figure 7.12. (the twelfth figure in chapter 7)

Whether you are using regular numbers or double numbering, use a period after the figure number to separate it from the caption text. 8

You may occasionally see the period omitted in favor of bold font combined with extra space before the caption text. 9 Like placing captions in uncommon locations, this decision is usually made by a layout designer or production editor rather than the writer or copy editor.

4. Use sentence-style capitalization.

Captions should feature sentence-style capitalization rather than headline-style capitalization . 10 This recommendation applies to complete sentences and to phrases and sentence fragments.

5. End captions with a period … most of the time.

Two of our primary style guides, the Publication Manual of the American Psychological Association (APA style) and the MLA Handbook (MLA style) use periods at the end of all captions even if they are incomplete sentences. 12

One of our other primary style guides, The Chicago Manual of Style (along with its academic version, Turabian) says that periods can be omitted if your captions are all phrases or sentence fragments. But, if your captions consist of complete sentences mixed with phrases and sentence fragments, always use periods. 13

6. Include a variety of information (if necessary).

A caption should briefly describe the figure. You can also include additional information such as copyright statements, source citations, definitions of symbols, and explanations of units of measurement. 14

There’s no official guideline for how long a caption can be. But, keep your readers in mind when writing captions because long blocks of unbroken text can be difficult to read (and therefore easy to ignore). If you think your caption is too long, consider other ways to present the necessary information, including the use of legends, labels, and keys within the figure itself.

7. Reference all figures in your text.

Each figure should be referenced in a sentence in your text, preferably before the figure appears in the document. The purpose of in-text references is to show your readers how figures connect to the content they are reading.

See “ How to Reference Figures and Tables in Sentences ” for examples and information relative to specific style guides.

The captions attached to figure 1 and figure 2, below, are examples based on the seven tips explained above.

Figure 1. Above left , Bartholomew; above right , Peabody; below left , Mr. Heckle; below right , Mr. Jeckle. Photography by Erin Wright.

Figure 2. Study participants’ favorite activities rated by occurrences per day. Reproduced by permission from Erin Wright, The Pets Are Running the Show (Whiting, IN: Fake Press, 2019), 57.

Related Resources

Three Ways to Insert Tables in Microsoft Word

How to Create and Customize Charts in Microsoft Word

How to Insert Figure Captions and Table Titles in Microsoft Word

How to Change the Style of Table Titles and Figure Captions in Microsoft Word

How to Update Table and Figure Numbers in Microsoft Word

How to Create and Update a List of Tables or Figures in Microsoft Word

How to Cross-Reference Tables and Figures in Microsoft Word

• Publication Manual of the American Psychological Association , 7th ed. (Washington, DC: American Psychological Association, 2020), 7.23–7.25.
• Publication Manual of the American Psychological Association , 6th ed. (Washington, DC: American Psychological Association, 2010), 5.23.
• AMA Manual of Style , 10th ed. (Oxford: Oxford University Press, 2007), 4.2.7.
• The Chicago Manual of Style , 17th ed. (Chicago: University of Chicago Press, 2017), 3.21. Publication Manual of the American Psychological Association , 5.23; “ Tables and Illustrations ,” Formatting a Research Paper, The MLA Style Center, accessed September 9, 2019; Kate L. Turabian, A Manual for Writers of Research Papers, Theses, and Dissertations , 9th ed. (Chicago: University of Chicago Press, 2018), 26.3.2.
• “ Headlines and Titles of Works ,” Style Q&A, The Chicago Manual of Style Online, accessed September 10, 2019.
• The Chicago Manual of Style , 3.5. “ Tables and Illustrations ,” The MLA Style Center.
• Turabian, A Manual for Writers of Research Papers, Theses, and Dissertations , 26.3.2.
• The Chicago Manual of Style , 3.23; Publication Manual of the American Psychological Association , 5.23; “ Tables and Illustrations ,” The MLA Style Center; Turabian, A Manual for Writers of Research Papers, Theses, and Dissertations , 26.3.2.
• The Chicago Manual of Style , 3.23.
• “ Tables and Illustrations ,” The MLA Style Center.
• The Chicago Manual of Style , 3.21; Publication Manual of the American Psychological Association , 5.23; Turabian, A Manual for Writers of Research Paper, Theses, and Dissertations , 26.3.3.2.
• Publication Manual of the American Psychological Association , 5.23; “ Tables and Illustrations ,” The MLA Style Center.
• The Chicago Manual of Style , 3.21; Turabian, A Manual for Writers of Research Papers, Theses, and Dissertations , 26.3.3.1.
• The Chicago Manual of Style , 3.25; Publication Manual of the American Psychological Association , 5.23; Turabian, A Manual for Writers of Research Papers, Theses, and Dissertations , 26.3.3.2
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