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Chapter 2: Descriptive Statistics

Chapter 2 Homework

Student grades on a chemistry exam were: 77, 78, 76, 81, 86, 51, 79, 82, 84, 99

  • Construct a stem-and-leaf plot of the data.
  • Are there any potential outliers? If so, which scores are they? Why do you consider them outliers?

[link] contains the 2010 obesity rates in U.S. states and Washington, DC.

  • Use a random number generator to randomly pick eight states. Construct a bar graph of the obesity rates of those eight states.
  • Construct a bar graph for all the states beginning with the letter “A.”
  • Construct a bar graph for all the states beginning with the letter “M.”
  • Number the entries in the table 1–51 (Includes Washington, DC; Numbered vertically)
  • Arrow over to PRB
  • Press 5:randInt(
  • Enter 51,1,8)

Eight numbers are generated (use the right arrow key to scroll through the numbers). The numbers correspond to the numbered states (for this example: {47 21 9 23 51 13 25 4}. If any numbers are repeated, generate a different number by using 5:randInt(51,1)). Here, the states (and Washington DC) are {Arkansas, Washington DC, Idaho, Maryland, Michigan, Mississippi, Virginia, Wyoming}.

Corresponding percents are {30.1, 22.2, 26.5, 27.1, 30.9, 34.0, 26.0, 25.1}.

A bar graph showing 8 states on the x-axis and corresponding obesity rates on the y-axis.

Homework from 2.2

Suppose that three book publishers were interested in the number of fiction paperbacks adult consumers purchase per month. Each publisher conducted a survey. In the survey, adult consumers were asked the number of fiction paperbacks they had purchased the previous month. The results are as follows:

  • Find the relative frequencies for each survey. Write them in the charts.
  • Using either a graphing calculator, computer, or by hand, use the frequency column to construct a histogram for each publisher’s survey. For Publishers A and B, make bar widths of one. For Publisher C, make bar widths of two.
  • In complete sentences, give two reasons why the graphs for Publishers A and B are not identical.
  • Would you have expected the graph for Publisher C to look like the other two graphs? Why or why not?
  • Make new histograms for Publisher A and Publisher B. This time, make bar widths of two.
  • Now, compare the graph for Publisher C to the new graphs for Publishers A and B. Are the graphs more similar or more different? Explain your answer.

Often, cruise ships conduct all on-board transactions, with the exception of gambling, on a cashless basis. At the end of the cruise, guests pay one bill that covers all onboard transactions. Suppose that 60 single travelers and 70 couples were surveyed as to their on-board bills for a seven-day cruise from Los Angeles to the Mexican Riviera. Following is a summary of the bills for each group.

  • Fill in the relative frequency for each group.
  • Construct a histogram for the singles group. Scale the x -axis by 💲50 widths. Use relative frequency on the y -axis.
  • Construct a histogram for the couples group. Scale the x -axis by 💲50 widths. Use relative frequency on the y -axis.
  • List two similarities between the graphs.
  • List two differences between the graphs.
  • Overall, are the graphs more similar or different?
  • Construct a new graph for the couples by hand. Since each couple is paying for two individuals, instead of scaling the x -axis by 💲50, scale it by 💲100. Use relative frequency on the y -axis.
  • How did scaling the couples graph differently change the way you compared it to the singles graph?
  • Based on the graphs, do you think that individuals spend the same amount, more or less, as singles as they do person by person as a couple? Explain why in one or two complete sentences.
  • See [link] and [link] .

This is a histogram that matches the supplied data supplied for singles. The x-axis shows the total charges in intervals of 50 from 50 to 350, and the y-axis shows the relative frequency in increments of 0.05 from 0 to 0.3.

  • Both graphs have a single peak.
  • Both graphs use class intervals with width equal to 💲50.
  • The couples graph has a class interval with no values.
  • It takes almost twice as many class intervals to display the data for couples.
  • Answers may vary. Possible answers include: The graphs are more similar than different because the overall patterns for the graphs are the same.
  • Check student’s solution.
  • Both graphs display 6 class intervals.
  • Both graphs show the same general pattern.
  • Answers may vary. Possible answers include: Although the width of the class intervals for couples is double that of the class intervals for singles, the graphs are more similar than they are different.
  • Answers may vary. Possible answers include: You are able to compare the graphs interval by interval. It is easier to compare the overall patterns with the new scale on the Couples graph. Because a couple represents two individuals, the new scale leads to a more accurate comparison.
  • Answers may vary. Possible answers include: Based on the histograms, it seems that spending does not vary much from singles to individuals who are part of a couple. The overall patterns are the same. The range of spending for couples is approximately double the range for individuals.

Twenty-five randomly selected students were asked the number of movies they watched the previous week. The results are as follows.

  • Construct a histogram of the data.
  • Complete the columns of the chart.

Use the following information to answer the next two exercises: Suppose one hundred eleven people who shopped in a special t-shirt store were asked the number of t-shirts they own costing more than 💲19 each.

A histogram showing the results of a survey. Of 111 respondents, 5 own 1 t-shirt costing more than 💲19, 17 own 2, 23 own 3, 39 own 4, 25 own 5, 2 own 6, and no respondents own 7.

The percentage of people who own at most three t-shirts costing more than 💲19 each is approximately:

  • Cannot be determined

If the data were collected by asking the first 111 people who entered the store, then the type of sampling is:

  • simple random
  • convenience

Following are the 2010 obesity rates by U.S. states and Washington, DC.

Construct a bar graph of obesity rates of your state and the four states closest to your state. Hint: Label the x -axis with the states.

Answers will vary.

Homework for 2.3

The median age for U.S. blacks currently is 30.9 years; for U.S. whites it is 42.3 years.

Six hundred adult Americans were asked by telephone poll, “What do you think constitutes a middle-class income?” The results are in [link] . Also, include left endpoint, but not the right endpoint.

  • What percentage of the survey answered “not sure”?
  • What percentage think that middle-class is from 💲25,000 to 💲50,000?
  • Should all bars have the same width, based on the data? Why or why not?
  • How should the <20,000 and the 100,000+ intervals be handled? Why?
  • Find the 40 th and 80 th percentiles
  • Construct a bar graph of the data
  • 1 – (0.02+0.09+0.19+0.26+0.18+0.17+0.02+0.01) = 0.06
  • 0.19+0.26+0.18 = 0.63

40 th percentile will fall between 30,000 and 40,000

80 th percentile will fall between 50,000 and 75,000

Given the following box plot:

This is a horizontal boxplot graphed over a number line from 0 to 13. The first whisker extends from the smallest value, 0, to the first quartile, 2. The box begins at the first quartile and extends to third quartile, 12. A vertical, dashed line is drawn at median, 10. The second whisker extends from the third quartile to largest value, 13.

  • which quarter has the smallest spread of data? What is that spread?
  • which quarter has the largest spread of data? What is that spread?
  • find the interquartile range ( IQR ).
  • are there more data in the interval 5–10 or in the interval 10–13? How do you know this?
  • need more information

The following box plot shows the U.S. population for 1990, the latest available year.

A box plot with values from 0 to 105, with Q1 at 17, M at 33, and Q3 at 50.

  • Are there fewer or more children (age 17 and under) than senior citizens (age 65 and over)? How do you know?
  • 12.6% are age 65 and over. Approximately what percentage of the population are working age adults (above age 17 to age 65)?
  • more children; the left whisker shows that 25% of the population are children 17 and younger. The right whisker shows that 25% of the population are adults 50 and older, so adults 65 and over represent less than 25%.

Homework from 2.4

In a survey of 20-year-olds in China, Germany, and the United States, people were asked the number of foreign countries they had visited in their lifetime. The following box plots display the results.

This shows three boxplots graphed over a number line from 0 to 11. The boxplots match the supplied data, and compare the countries' results. The China boxplot has a single whisker from 0 to 5. The Germany box plot's median is equal to the third quartile, so there is a dashed line at right edge of box. The America boxplot does not have a left whisker.

  • In complete sentences, describe what the shape of each box plot implies about the distribution of the data collected.
  • Have more Americans or more Germans surveyed been to over eight foreign countries?
  • Compare the three box plots. What do they imply about the foreign travel of 20-year-old residents of the three countries when compared to each other?

Given the following box plot, answer the questions.

This is a boxplot graphed over a number line from 0 to 150. There is no first, or left, whisker. The box starts at the first quartile, 0, and ends at the third quartile, 80. A vertical, dashed line marks the median, 20. The second whisker extends the third quartile to the largest value, 150.

  • Think of an example (in words) where the data might fit into the above box plot. In 2–5 sentences, write down the example.
  • What does it mean to have the first and second quartiles so close together, while the second to third quartiles are far apart?
  • Answers will vary. Possible answer: State University conducted a survey to see how involved its students are in community service. The box plot shows the number of community service hours logged by participants over the past year.
  • Because the first and second quartiles are close, the data in this quarter is very similar. There is not much variation in the values. The data in the third quarter is much more variable, or spread out. This is clear because the second quartile is so far away from the third quartile.

Given the following box plots, answer the questions.

This shows two boxplots graphed over number lines from 0 to 7. The first whisker in the data 1 boxplot extends from 0 to 2. The box begins at the firs quartile, 2, and ends at the third quartile, 5. A vertical, dashed line marks the median at 4. The second whisker extends from the third quartile to the largest value, 7. The first whisker in the data 2 box plot extends from 0 to 1.3. The box begins at the first quartile, 1.3, and ends at the third quartile, 2.5. A vertical, dashed line marks the medial at 2. The second whisker extends from the third quartile to the largest value, 7.

  • Data 1 has more data values above two than Data 2 has above two.
  • The data sets cannot have the same mode.
  • For Data 1 , there are more data values below four than there are above four.
  • For which group, Data 1 or Data 2, is the value of “7” more likely to be an outlier? Explain why in complete sentences.

A survey was conducted of 130 purchasers of new BMW 3 series cars, 130 purchasers of new BMW 5 series cars, and 130 purchasers of new BMW 7 series cars. In it, people were asked the age they were when they purchased their car. The following box plots display the results.

This shows three boxplots graphed over a number line from 25 to 80. The first whisker on the BMW 3 plot extends from 25 to 30. The box begins at the firs quartile, 30 and ends at the thir quartile, 41. A verical, dashed line marks the median at 34. The second whisker extends from the third quartile to 66. The first whisker on the BMW 5 plot extends from 31 to 40. The box begins at the firs quartile, 40, and ends at the third quartile, 55. A vertical, dashed line marks the median at 41. The second whisker extends from 55 to 64. The first whisker on the BMW 7 plot extends from 35 to 41. The box begins at the first quartile, 41, and ends at the third quartile, 59. A vertical, dashed line marks the median at 46. The second whisker extends from 59 to 68.

  • In complete sentences, describe what the shape of each box plot implies about the distribution of the data collected for that car series.
  • Which group is most likely to have an outlier? Explain how you determined that.
  • Compare the three box plots. What do they imply about the age of purchasing a BMW from the series when compared to each other?
  • Look at the BMW 5 series. Which quarter has the smallest spread of data? What is the spread?
  • Look at the BMW 5 series. Which quarter has the largest spread of data? What is the spread?
  • Look at the BMW 5 series. Estimate the interquartile range (IQR).
  • Look at the BMW 5 series. Are there more data in the interval 31 to 38 or in the interval 45 to 55? How do you know this?
  • Each box plot is spread out more in the greater values. Each plot is skewed to the right, so the ages of the top 50% of buyers are more variable than the ages of the lower 50%.
  • The BMW 3 series is most likely to have an outlier. It has the longest whisker.
  • Comparing the median ages, younger people tend to buy the BMW 3 series, while older people tend to buy the BMW 7 series. However, this is not a rule, because there is so much variability in each data set.
  • The second quarter has the smallest spread. There seems to be only a three-year difference between the first quartile and the median.
  • The third quarter has the largest spread. There seems to be approximately a 14-year difference between the median and the third quartile.
  • IQR ~ 17 years
  • There is not enough information to tell. Each interval lies within a quarter, so we cannot tell exactly where the data in that quarter is concentrated.
  • The interval from 31 to 35 years has the fewest data values. Twenty-five percent of the values fall in the interval 38 to 41, and 25% fall between 41 and 64. Since 25% of values fall between 31 and 38, we know that fewer than 25% fall between 31 and 35.

Twenty-five randomly selected students were asked the number of movies they watched the previous week. The results are as follows:

Construct a box plot of the data.

Homework from 2.5

The most obese countries in the world have obesity rates that range from 11.4% to 74.6%. This data is summarized in the following table.

  • What is the best estimate of the average obesity percentage for these countries?
  • The United States has an average obesity rate of 33.9%. Is this rate above average or below?
  • How does the United States compare to other countries?

[link] gives the percent of children under five considered to be underweight. What is the best estimate for the mean percentage of underweight children?

The mean percentage, [latex]\overline{x}=\frac{1328.65}{50}=26.75[/latex]

Homework for 2.6

The median age of the U.S. population in 1980 was 30.0 years. In 1991, the median age was 33.1 years.

  • What does it mean for the median age to rise?
  • Give two reasons why the median age could rise.
  • For the median age to rise, is the actual number of children less in 1991 than it was in 1980? Why or why not?

Homework from 2.7

Use the following information to answer the next nine exercises: The population parameters below describe the full-time equivalent number of students (FTES) each year at Lake Tahoe Community College from 1976–1977 through 2004–2005.

  • μ = 1000 FTES
  • median = 1,014 FTES
  • σ = 474 FTES
  • first quartile = 528.5 FTES
  • third quartile = 1,447.5 FTES
  • n = 29 years

A sample of 11 years is taken. About how many are expected to have a FTES of 1014 or above? Explain how you determined your answer.

The median value is the middle value in the ordered list of data values. The median value of a set of 11 will be the 6th number in order. Six years will have totals at or below the median.

75% of all years have an FTES:

The population standard deviation = _____

What percent of the FTES were from 528.5 to 1447.5? How do you know?

What is the IQR ? What does the IQR represent?

How many standard deviations away from the mean is the median?

Additional Information: The population FTES for 2005–2006 through 2010–2011 was given in an updated report. The data are reported here.

Calculate the mean, median, standard deviation, the first quartile, the third quartile and the IQR . Round to one decimal place.

  • mean = 1,809.3
  • median = 1,812.5
  • standard deviation = 151.2
  • first quartile = 1,690
  • third quartile = 1,935

Construct a box plot for the FTES for 2005–2006 through 2010–2011 and a box plot for the FTES for 1976–1977 through 2004–2005.

Compare the IQR for the FTES for 1976–77 through 2004–2005 with the IQR for the FTES for 2005-2006 through 2010–2011. Why do you suppose the IQR s are so different?

Hint: Think about the number of years covered by each time period and what happened to higher education during those periods.

Three students were applying to the same graduate school. They came from schools with different grading systems. Which student had the best GPA when compared to other students at his school? Explain how you determined your answer.

A music school has budgeted to purchase three musical instruments. They plan to purchase a piano costing 💲3,000, a guitar costing 💲550, and a drum set costing 💲600. The mean cost for a piano is 💲4,000 with a standard deviation of 💲2,500. The mean cost for a guitar is 💲500 with a standard deviation of 💲200. The mean cost for drums is 💲700 with a standard deviation of 💲100. Which cost is the lowest, when compared to other instruments of the same type? Which cost is the highest when compared to other instruments of the same type. Justify your answer.

For pianos, the cost of the piano is 0.4 standard deviations BELOW the mean. For guitars, the cost of the guitar is 0.25 standard deviations ABOVE the mean. For drums, the cost of the drum set is 1.0 standard deviations BELOW the mean. Of the three, the drums cost the lowest in comparison to the cost of other instruments of the same type. The guitar costs the most in comparison to the cost of other instruments of the same type.

An elementary school class ran one mile with a mean of 11 minutes and a standard deviation of three minutes. Rachel, a student in the class, ran one mile in eight minutes. A junior high school class ran one mile with a mean of nine minutes and a standard deviation of two minutes. Kenji, a student in the class, ran 1 mile in 8.5 minutes. A high school class ran one mile with a mean of seven minutes and a standard deviation of four minutes. Nedda, a student in the class, ran one mile in eight minutes.

  • Why is Kenji considered a better runner than Nedda, even though Nedda ran faster than he?
  • Who is the fastest runner with respect to his or her class? Explain why.

The most obese countries in the world have obesity rates that range from 11.4% to 74.6%. This data is summarized in Table 14 .

What is the best estimate of the average obesity percentage for these countries? What is the standard deviation for the listed obesity rates? The United States has an average obesity rate of 33.9%. Is this rate above average or below? How “unusual” is the United States’ obesity rate compared to the average rate? Explain.

  • [latex]\overline{x}=23.32[/latex]
  • Using the TI 83/84, we obtain a standard deviation of: [latex]{s}_{x}=12.95.[/latex]
  • The obesity rate of the United States is 10.58% higher than the average obesity rate.
  • Since the standard deviation is 12.95, we see that 23.32 + 12.95 = 36.27 is the obesity percentage that is one standard deviation from the mean. The United States obesity rate is slightly less than one standard deviation from the mean. Therefore, we can assume that the United States, while 34% obese, does not hav e an unusually high percentage of obese people.

[link] gives the percent of children under five considered to be underweight.

What is the best estimate for the mean percentage of underweight children? What is the standard deviation? Which interval(s) could be considered unusual? Explain.

used to describe data that is not symmetrical; when the right side of a graph looks “chopped off” compared the left side, we say it is “skewed to the left.” When the left side of the graph looks “chopped off” compared to the right side, we say the data is “skewed to the right.” Alternatively: when the lower values of the data are more spread out, we say the data are skewed to the left. When the greater values are more spread out, the data are skewed to the right.

Introductory Statistics Copyright © by Jared Eusea; Phyllis Okwan; Rachid Belmasrour; Stephan Patterson; and Stephen Andrus is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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  • Introduction
  • 1.1 Definitions of Statistics, Probability, and Key Terms
  • 1.2 Data, Sampling, and Variation in Data and Sampling
  • 1.3 Frequency, Frequency Tables, and Levels of Measurement
  • 1.4 Experimental Design and Ethics
  • 1.5 Data Collection Experiment
  • 1.6 Sampling Experiment
  • Chapter Review
  • Bringing It Together: Homework
  • 2.1 Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
  • 2.2 Histograms, Frequency Polygons, and Time Series Graphs
  • 2.3 Measures of the Location of the Data
  • 2.4 Box Plots
  • 2.5 Measures of the Center of the Data
  • 2.6 Skewness and the Mean, Median, and Mode
  • 2.7 Measures of the Spread of the Data
  • 2.8 Descriptive Statistics
  • Formula Review
  • 3.1 Terminology
  • 3.2 Independent and Mutually Exclusive Events
  • 3.3 Two Basic Rules of Probability
  • 3.4 Contingency Tables
  • 3.5 Tree and Venn Diagrams
  • 3.6 Probability Topics
  • Bringing It Together: Practice
  • 4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
  • 4.2 Mean or Expected Value and Standard Deviation
  • 4.3 Binomial Distribution
  • 4.4 Geometric Distribution
  • 4.5 Hypergeometric Distribution
  • 4.6 Poisson Distribution
  • 4.7 Discrete Distribution (Playing Card Experiment)
  • 4.8 Discrete Distribution (Lucky Dice Experiment)
  • 5.1 Continuous Probability Functions
  • 5.2 The Uniform Distribution
  • 5.3 The Exponential Distribution
  • 5.4 Continuous Distribution
  • 6.1 The Standard Normal Distribution
  • 6.2 Using the Normal Distribution
  • 6.3 Normal Distribution (Lap Times)
  • 6.4 Normal Distribution (Pinkie Length)
  • 7.1 The Central Limit Theorem for Sample Means (Averages)
  • 7.2 The Central Limit Theorem for Sums
  • 7.3 Using the Central Limit Theorem
  • 7.4 Central Limit Theorem (Pocket Change)
  • 7.5 Central Limit Theorem (Cookie Recipes)
  • 8.1 A Single Population Mean using the Normal Distribution
  • 8.2 A Single Population Mean using the Student t Distribution
  • 8.3 A Population Proportion
  • 8.4 Confidence Interval (Home Costs)
  • 8.5 Confidence Interval (Place of Birth)
  • 8.6 Confidence Interval (Women's Heights)
  • 9.1 Null and Alternative Hypotheses
  • 9.2 Outcomes and the Type I and Type II Errors
  • 9.3 Distribution Needed for Hypothesis Testing
  • 9.4 Rare Events, the Sample, Decision and Conclusion
  • 9.5 Additional Information and Full Hypothesis Test Examples
  • 9.6 Hypothesis Testing of a Single Mean and Single Proportion
  • 10.1 Two Population Means with Unknown Standard Deviations
  • 10.2 Two Population Means with Known Standard Deviations
  • 10.3 Comparing Two Independent Population Proportions
  • 10.4 Matched or Paired Samples
  • 10.5 Hypothesis Testing for Two Means and Two Proportions
  • 11.1 Facts About the Chi-Square Distribution
  • 11.2 Goodness-of-Fit Test
  • 11.3 Test of Independence
  • 11.4 Test for Homogeneity
  • 11.5 Comparison of the Chi-Square Tests
  • 11.6 Test of a Single Variance
  • 11.7 Lab 1: Chi-Square Goodness-of-Fit
  • 11.8 Lab 2: Chi-Square Test of Independence
  • 12.1 Linear Equations
  • 12.2 Scatter Plots
  • 12.3 The Regression Equation
  • 12.4 Testing the Significance of the Correlation Coefficient
  • 12.5 Prediction
  • 12.6 Outliers
  • 12.7 Regression (Distance from School)
  • 12.8 Regression (Textbook Cost)
  • 12.9 Regression (Fuel Efficiency)
  • 13.1 One-Way ANOVA
  • 13.2 The F Distribution and the F-Ratio
  • 13.3 Facts About the F Distribution
  • 13.4 Test of Two Variances
  • 13.5 Lab: One-Way ANOVA
  • A | Review Exercises (Ch 3-13)
  • B | Practice Tests (1-4) and Final Exams
  • C | Data Sets
  • D | Group and Partner Projects
  • E | Solution Sheets
  • F | Mathematical Phrases, Symbols, and Formulas
  • G | Notes for the TI-83, 83+, 84, 84+ Calculators

The relative frequency shows the proportion of data points that have each value. The frequency tells the number of data points that have each value.

Answers will vary. One possible histogram is shown:

Find the midpoint for each class. These will be graphed on the x -axis. The frequency values will be graphed on the y -axis values.

  • The 40 th percentile is 37 years.
  • The 78 th percentile is 70 years.

Jesse graduated 37 th out of a class of 180 students. There are 180 – 37 = 143 students ranked below Jesse. There is one rank of 37.

x = 143 and y = 1. x + 0.5 y n x + 0.5 y n (100) = 143 + 0.5 ( 1 ) 180 143 + 0.5 ( 1 ) 180 (100) = 79.72. Jesse’s rank of 37 puts him at the 80 th percentile.

  • For runners in a race it is more desirable to have a high percentile for speed. A high percentile means a higher speed which is faster.
  • 40% of runners ran at speeds of 7.5 miles per hour or less (slower). 60% of runners ran at speeds of 7.5 miles per hour or more (faster).

When waiting in line at the DMV, the 85 th percentile would be a long wait time compared to the other people waiting. 85% of people had shorter wait times than Mina. In this context, Mina would prefer a wait time corresponding to a lower percentile. 85% of people at the DMV waited 32 minutes or less. 15% of people at the DMV waited 32 minutes or longer.

The manufacturer and the consumer would be upset. This is a large repair cost for the damages, compared to the other cars in the sample. INTERPRETATION: 90% of the crash tested cars had damage repair costs of $1700 or less; only 10% had damage repair costs of $1700 or more.

You can afford 34% of houses. 66% of the houses are too expensive for your budget. INTERPRETATION: 34% of houses cost $240,000 or less. 66% of houses cost $240,000 or more.

More than 25% of salespersons sell four cars in a typical week. You can see this concentration in the box plot because the first quartile is equal to the median. The top 25% and the bottom 25% are spread out evenly; the whiskers have the same length.

Mean: 16 + 17 + 19 + 20 + 20 + 21 + 23 + 24 + 25 + 25 + 25 + 26 + 26 + 27 + 27 + 27 + 28 + 29 + 30 + 32 + 33 + 33 + 34 + 35 + 37 + 39 + 40 = 738;

738 27 738 27 = 27.33

The most frequent lengths are 25 and 27, which occur three times. Mode = 25, 27

The data are symmetrical. The median is 3 and the mean is 2.85. They are close, and the mode lies close to the middle of the data, so the data are symmetrical.

The data are skewed right. The median is 87.5 and the mean is 88.2. Even though they are close, the mode lies to the left of the middle of the data, and there are many more instances of 87 than any other number, so the data are skewed right.

When the data are symmetrical, the mean and median are close or the same.

The distribution is skewed right because it looks pulled out to the right.

The mean is 4.1 and is slightly greater than the median, which is four.

The mode and the median are the same. In this case, they are both five.

The distribution is skewed left because it looks pulled out to the left.

The mean and the median are both six.

The mode is 12, the median is 12.5, and the mean is 15.1. The mean is the largest.

The mean tends to reflect skewing the most because it is affected the most by outliers.

For Fredo: z = 0.158  –  0.166 0.012 0.158  –  0.166 0.012 = –0.67

For Karl: z = 0.177  –  0.189 0.015 0.177  –  0.189 0.015 = –0.8

Fredo’s z -score of –0.67 is higher than Karl’s z -score of –0.8. For batting average, higher values are better, so Fredo has a better batting average compared to his team.

  • s x = ∑ f m 2 n − x ¯ 2 = 193157.45 30 − 79.5 2 = 10.88 s x = ∑ f m 2 n − x ¯ 2 = 193157.45 30 − 79.5 2 = 10.88
  • s x = ∑ f m 2 n − x ¯ 2 = 380945.3 101 − 60.94 2 = 7.62 s x = ∑ f m 2 n − x ¯ 2 = 380945.3 101 − 60.94 2 = 7.62
  • s x = ∑ f m 2 n − x ¯ 2 = 440051.5 86 − 70.66 2 = 11.14 s x = ∑ f m 2 n − x ¯ 2 = 440051.5 86 − 70.66 2 = 11.14
  • Number the entries in the table 1–51 (Includes Washington, DC; Numbered vertically)
  • Arrow over to PRB
  • Press 5:randInt(
  • Enter 51,1,8)

Eight numbers are generated (use the right arrow key to scroll through the numbers). The numbers correspond to the numbered states (for this example: {47 21 9 23 51 13 25 4}. If any numbers are repeated, generate a different number by using 5:randInt(51,1)). Here, the states (and Washington DC) are {Arkansas, Washington DC, Idaho, Maryland, Michigan, Mississippi, Virginia, Wyoming}.

Corresponding percents are {30.1, 22.2, 26.5, 27.1, 30.9, 34.0, 26.0, 25.1}.

  • See Table 2.86 and Table 2.87 .
  • Both graphs have a single peak.
  • Both graphs use class intervals with width equal to $50.
  • The couples graph has a class interval with no values.
  • It takes almost twice as many class intervals to display the data for couples.
  • Answers may vary. Possible answers include: The graphs are more similar than different because the overall patterns for the graphs are the same.
  • Check student's solution.
  • Both graphs display 6 class intervals.
  • Both graphs show the same general pattern.
  • Answers may vary. Possible answers include: Although the width of the class intervals for couples is double that of the class intervals for singles, the graphs are more similar than they are different.
  • Answers may vary. Possible answers include: You are able to compare the graphs interval by interval. It is easier to compare the overall patterns with the new scale on the Couples graph. Because a couple represents two individuals, the new scale leads to a more accurate comparison.
  • Answers may vary. Possible answers include: Based on the histograms, it seems that spending does not vary much from singles to individuals who are part of a couple. The overall patterns are the same. The range of spending for couples is approximately double the range for individuals.

Answers will vary.

  • 1 – (0.02+0.09+0.19+0.26+0.18+0.17+0.02+0.01) = 0.06
  • 0.19+0.26+0.18 = 0.63
  • Check student’s solution.

40 th percentile will fall between 30,000 and 40,000

80 th percentile will fall between 50,000 and 75,000

  • more children; the left whisker shows that 25% of the population are children 17 and younger. The right whisker shows that 25% of the population are adults 50 and older, so adults 65 and over represent less than 25%.
  • Answers will vary. Possible answer: State University conducted a survey to see how involved its students are in community service. The box plot shows the number of community service hours logged by participants over the past year.
  • Because the first and second quartiles are close, the data in this quarter is very similar. There is not much variation in the values. The data in the third quarter is much more variable, or spread out. This is clear because the second quartile is so far away from the third quartile.
  • Each box plot is spread out more in the greater values. Each plot is skewed to the right, so the ages of the top 50% of buyers are more variable than the ages of the lower 50%.
  • The BMW 3 series is most likely to have an outlier. It has the longest whisker.
  • Comparing the median ages, younger people tend to buy the BMW 3 series, while older people tend to buy the BMW 7 series. However, this is not a rule, because there is so much variability in each data set.
  • The second quarter has the smallest spread. There seems to be only a three-year difference between the first quartile and the median.
  • The third quarter has the largest spread. There seems to be approximately a 14-year difference between the median and the third quartile.
  • IQR ~ 17 years
  • There is not enough information to tell. Each interval lies within a quarter, so we cannot tell exactly where the data in that quarter is concentrated.
  • The interval from 31 to 35 years has the fewest data values. Twenty-five percent of the values fall in the interval 38 to 41, and 25% fall between 41 and 64. Since 25% of values fall between 31 and 38, we know that fewer than 25% fall between 31 and 35.

The mean percentage, x ¯ = 1328.65 50 = 26.75 x ¯ = 1328.65 50 = 26.75

The median value is the middle value in the ordered list of data values. The median value of a set of 11 will be the 6th number in order. Six years will have totals at or below the median.

  • mean = 1,809.3
  • median = 1,812.5
  • standard deviation = 151.2
  • first quartile = 1,690
  • third quartile = 1,935

Hint: Think about the number of years covered by each time period and what happened to higher education during those periods.

For pianos, the cost of the piano is 0.4 standard deviations BELOW the mean. For guitars, the cost of the guitar is 0.25 standard deviations ABOVE the mean. For drums, the cost of the drum set is 1.0 standard deviations BELOW the mean. Of the three, the drums cost the lowest in comparison to the cost of other instruments of the same type. The guitar costs the most in comparison to the cost of other instruments of the same type.

  • x ¯ = 23.32 x ¯ = 23.32
  • Using the TI 83/84, we obtain a standard deviation of: s x = 12.95. s x = 12.95.
  • The obesity rate of the United States is 10.58% higher than the average obesity rate.
  • Since the standard deviation is 12.95, we see that 23.32 + 12.95 = 36.27 is the obesity percentage that is one standard deviation from the mean. The United States obesity rate is slightly less than one standard deviation from the mean. Therefore, we can assume that the United States, while 34% obese, does not hav e an unusually high percentage of obese people.
  • For graph, check student's solution.
  • 49.7% of the community is under the age of 35.
  • Based on the information in the table, graph (a) most closely represents the data.
  • 174; 177; 178; 184; 185; 185; 185; 185; 188; 190; 200; 205; 205; 206; 210; 210; 210; 212; 212; 215; 215; 220; 223; 228; 230; 232; 241; 241; 242; 245; 247; 250; 250; 259; 260; 260; 265; 265; 270; 272; 273; 275; 276; 278; 280; 280; 285; 285; 286; 290; 290; 295; 302
  • 205.5, 272.5
  • 0.84 std. dev. below the mean

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Access for free at https://openstax.org/books/introductory-statistics/pages/1-introduction
  • Authors: Barbara Illowsky, Susan Dean
  • Publisher/website: OpenStax
  • Book title: Introductory Statistics
  • Publication date: Sep 19, 2013
  • Location: Houston, Texas
  • Book URL: https://openstax.org/books/introductory-statistics/pages/1-introduction
  • Section URL: https://openstax.org/books/introductory-statistics/pages/2-solutions

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COMMENTS

  1. Statistics Math 125

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  2. Statistics: Section 2.1 Flashcards

    1. The pie chart below depicts the beverage size customers choose while at a fast food restaurant. Complete parts (a) through (c). A pie chart titled "Most popular beverage sizes at a restaurant" contains four sectors, each labeled with a beverage size and a percentage as follows: Small, 22%; Medium, 16%; Large, 52%; XL, 10%.

  3. Ch. 2 Homework

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  4. Chapter 2.1 Solutions

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