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Published 2008 Revised 2019

Understanding Hypotheses

'What happens if ... ?' to ' This will happen if'

The experimentation of children continually moves on to the exploration of new ideas and the refinement of their world view of previously understood situations. This description of the playtime patterns of young children very nicely models the concept of 'making and testing hypotheses'. It follows this pattern:

• Make some observations. Collect some data based on the observations.
• Draw a conclusion (called a 'hypothesis') which will explain the pattern of the observations.
• Test out your hypothesis by making some more targeted observations.

So, we have

• A hypothesis is a statement or idea which gives an explanation to a series of observations.

Sometimes, following observation, a hypothesis will clearly need to be refined or rejected. This happens if a single contradictory observation occurs. For example, suppose that a child is trying to understand the concept of a dog. He reads about several dogs in children's books and sees that they are always friendly and fun. He makes the natural hypothesis in his mind that dogs are friendly and fun . He then meets his first real dog: his neighbour's puppy who is great fun to play with. This reinforces his hypothesis. His cousin's dog is also very friendly and great fun. He meets some of his friends' dogs on various walks to playgroup. They are also friendly and fun. He is now confident that his hypothesis is sound. Suddenly, one day, he sees a dog, tries to stroke it and is bitten. This experience contradicts his hypothesis. He will need to amend the hypothesis. We see that

• Gathering more evidence/data can strengthen a hypothesis if it is in agreement with the hypothesis.
• If the data contradicts the hypothesis then the hypothesis must be rejected or amended to take into account the contradictory situation.

• A contradictory observation can cause us to know for certain that a hypothesis is incorrect.
• Accumulation of supporting experimental evidence will strengthen a hypothesis but will never let us know for certain that the hypothesis is true.

In short, it is possible to show that a hypothesis is false, but impossible to prove that it is true!

Whilst we can never prove a scientific hypothesis to be true, there will be a certain stage at which we decide that there is sufficient supporting experimental data for us to accept the hypothesis. The point at which we make the choice to accept a hypothesis depends on many factors. In practice, the key issues are

• What are the implications of mistakenly accepting a hypothesis which is false?
• What are the cost / time implications of gathering more data?
• What are the implications of not accepting in a timely fashion a true hypothesis?

For example, suppose that a drug company is testing a new cancer drug. They hypothesise that the drug is safe with no side effects. If they are mistaken in this belief and release the drug then the results could have a disastrous effect on public health. However, running extended clinical trials might be very costly and time consuming. Furthermore, a delay in accepting the hypothesis and releasing the drug might also have a negative effect on the health of many people.

In short, whilst we can never achieve absolute certainty with the testing of hypotheses, in order to make progress in science or industry decisions need to be made. There is a fine balance to be made between action and inaction.

Hypotheses and mathematics So where does mathematics enter into this picture? In many ways, both obvious and subtle:

• A good hypothesis needs to be clear, precisely stated and testable in some way. Creation of these clear hypotheses requires clear general mathematical thinking.
• The data from experiments must be carefully analysed in relation to the original hypothesis. This requires the data to be structured, operated upon, prepared and displayed in appropriate ways. The levels of this process can range from simple to exceedingly complex.

Very often, the situation under analysis will appear to be complicated and unclear. Part of the mathematics of the task will be to impose a clear structure on the problem. The clarity of thought required will actively be developed through more abstract mathematical study. Those without sufficient general mathematical skill will be unable to perform an appropriate logical analysis.

Using deductive reasoning in hypothesis testing

There is often confusion between the ideas surrounding proof, which is mathematics, and making and testing an experimental hypothesis, which is science. The difference is rather simple:

• Mathematics is based on deductive reasoning : a proof is a logical deduction from a set of clear inputs.
• Science is based on inductive reasoning : hypotheses are strengthened or rejected based on an accumulation of experimental evidence.

Of course, to be good at science, you need to be good at deductive reasoning, although experts at deductive reasoning need not be mathematicians. Detectives, such as Sherlock Holmes and Hercule Poirot, are such experts: they collect evidence from a crime scene and then draw logical conclusions from the evidence to support the hypothesis that, for example, Person M. committed the crime. They use this evidence to create sufficiently compelling deductions to support their hypotheses beyond reasonable doubt . The key word here is 'reasonable'. There is always the possibility of creating an exceedingly outlandish scenario to explain away any hypothesis of a detective or prosecution lawyer, but judges and juries in courts eventually make the decision that the probability of such eventualities are 'small' and the chance of the hypothesis being correct 'high'.

• If a set of data is normally distributed with mean 0 and standard deviation 0.5 then there is a 97.7% certainty that a measurement will not exceed 1.0.
• If the mean of a sample of data is 12, how confident can we be that the true mean of the population lies between 11 and 13?

It is at this point that making and testing hypotheses becomes a true branch of mathematics. This mathematics is difficult, but fascinating and highly relevant in the information-rich world of today.

To read more about the technical side of hypothesis testing, take a look at What is a Hypothesis Test?

You might also enjoy reading the articles on statistics on the Understanding Uncertainty website

This resource is part of the collection Statistics - Maths of Real Life

Writing a Hypothesis & Prediction

A prediction and a hypothesis are different. However, experiments should include both a hypothesis and a prediction.

• A hypothesis is normally generated from an idea or observation.

Examples of hypotheses

• Adding water to a sunflower will help it grow.
• An increase in temperature will increase the rate of reaction.
• A change in pH will affect how an enzyme works.

• The prediction will explain how your hypothesis can be tested.
• The prediction states a relationship between two variables.
• The stated relationship should be suggested in the hypothesis.

Examples of predictions

• If I increase the amount of water I use to water the plant, it will grow more.
• If I decrease the temperature, the rate of reaction will decrease.
• If I increase the pH, the rate of activity will increase.

The word 'because'

• Once you have written the prediction, you can extend your work by using the word ‘because’.
• Use your scientific knowledge to explain your prediction.

1.1 Cells, Tissues & Organs

1.1.1 Microscopes

1.1.2 Magnification

1.1.3 Multicellular Organisms

1.1.4 Tissues

1.1.5 Organs

1.1.6 Unicellular Organisms

1.1.7 Diffusion

1.1.8 Factors Affecting Diffusion

1.1.9 Plant Cells

1.1.10 Cellulose

1.1.11 Plant Tissues

1.1.12 Leaves

1.1.13 Animal Cells

1.1.14 Comparing Animal & Plant Cells

1.1.15 How to Make a Model Animal and Plant Cell

1.1.16 Specialised Cells

1.1.17 Stem Cells

1.1.18 Uses of Stem Cells

1.1.19 Disadvantages of Stem Cells

1.1.20 Blood Components

1.1.21 Platelets

1.1.22 End of Topic Test - Cells & Organisation

1.1.23 The Lungs

1.1.24 Breathing

1.1.25 Plant Gas Exchange

1.1.26 Health

1.1.27 End of Topic Test - Living Organisms

1.2 Reproduction & Variation

1.2.1 Reproduction in Humans

1.2.2 Male Reproductive System

1.2.3 Female Reproductive System

1.2.4 Gestation

1.2.5 Pregnancy

1.2.6 Puberty

1.2.7 The Menstrual Cycle

1.2.8 Reproduction in Plants

1.2.9 Pollination

1.2.10 Dispersal Method

1.2.11 Variation

1.2.12 Causes of Variation

1.2.13 Inheritance

1.2.14 Adaptations and Evolution

1.2.15 Species & Selective Breeding

1.2.16 Genetic Conditions

1.2.17 End of Topic Test - Reproduction & Variation

1.3 Ecological Relationships & Classification

1.3.1 Species Interdependence

1.3.2 Food Chains & Webs

1.3.3 Changes to Food Webs

1.3.4 Relationships in an Ecosystem

1.3.5 The Impact of Environmental Change

1.3.6 Decomposers

1.3.7 Decay

1.3.8 Assessing Ecosystems

1.3.9 Ecological Sampling

1.3.10 Required Practical - Estimating Population Size

1.3.11 Pyramids of Number and Biomass

1.3.12 Classification of Living Organisms

1.3.13 Competition Between Organisms

1.3.14 Adaptations of Plants

1.3.15 Natural Selection

1.3.16 Evidence for Evolution

1.3.17 Environmental Changes & Extinctions

1.3.18 The Importance of Biodiversity

1.3.19 Bioaccumulation

1.3.20 End of Topic Test - Material Cycles & Energy

1.4 Digestion & Nutrition

1.4.1 Balanced Diets

1.4.2 Vitamins & Minerals

1.4.3 Protein

1.4.4 Lipids, Oils and Fats

1.4.5 Carbohydrates

1.4.6 Starch

1.4.7 Energy Needs

1.4.8 Dietary Fibre

1.4.9 Diseases Caused by Nutritional Deficiencies

1.4.10 Digestion

1.4.11 Plant Nutrition

1.4.12 Enzymes in Digestion

1.4.13 Required Practical - Enzymes in Digestion

1.5 Plants & Photosynthesis

1.5.1 Roots

1.5.2 Photosynthesis

1.5.3 Leaves

1.5.4 Rate of Photosynthesis

1.5.5 Testing the Rate of Photosynthesis

1.5.6 Water Transport in Plants

1.5.7 Translocation

1.5.8 The Carbon Cycle

1.5.9 Human Activities & Carbon Dioxide

1.6 Biological Systems & Processes

1.6.1 Living Organisms

1.6.2 Dichotomous Keys

1.6.3 Biomechanics

1.6.4 Muscles

1.6.5 The Skeleton

1.6.6 Measuring Forces

1.6.7 Antagonistic Muscle Pairings

1.6.8 The Respiratory System

1.6.9 Structure & Function of the Gas Exchange System

1.6.10 Breathing

1.6.11 Respiration

1.6.12 Respiration During Exercise

1.6.13 Anaerobic Respiration

1.6.14 Lactic Acid

1.6.15 Effects of Smoking on the Respiratory System

1.6.16 Balanced Diets

1.6.17 Human Growth & Development

1.6.19 Alleles

1.6.20 Genotype vs Phenotype

1.6.21 Punnett Squares

1.6.22 Joints

1.6.23 The Renal System

1.6.24 The Circulatory System

1.6.25 The Circulatory System

1.6.26 Glucose

1.6.27 Glucose and Diabetes

1.6.28 The Effects of Recreational Drug Use

1.6.29 Human Illnesses

1.6.30 Antibiotics

1.6.31 Vaccinations

1.6.32 How Antibiotics and Vaccines Work

1.6.33 Mental Health

2 Chemistry

2.1 Particles

2.1.1 Particles

2.1.2 States of Matter

2.1.3 Changes of State

2.1.4 Properties of States of Matter

2.1.5 Diffusion

2.1.6 Changing State

2.1.7 Pressure

2.1.8 Temperature Increase in a Gas

2.1.9 Conservation of Mass

2.1.10 Purity of Substances

2.1.11 Pure Substances

2.1.12 Evaporation

2.1.13 Mixtures

2.1.14 Separating Mixtures

2.1.15 Distillation

2.1.16 Chromatography

2.1.17 Solubility

2.1.18 Investigating Solubility

2.2 Chemical Reactions

2.2.1 Chemical Reactions

2.2.2 Common Reactions

2.2.3 Acids & Alkalis

2.2.4 Reactions of Acids

2.2.5 Testing for Hydrogen

2.2.6 The pH Scale

2.2.7 Titration

2.2.8 End of Topic Test - Chemical Reactions

2.3 Atoms, Elements, Compounds

2.3.1 Atoms

2.3.2 Elements

2.3.3 Compounds & Mixtures

2.3.4 Electron Configuration

2.3.5 Chemical Symbols

2.3.6 Chemical Formulae

2.3.7 Conservation of Mass

2.3.8 Vacuums

2.3.9 Molecules

2.3.10 End of Topic Test - Particles & Atoms

2.4 The Periodic Table

2.4.1 Physical Properties

2.4.2 Chemical Properties

2.4.3 The Periodic Table

2.4.4 Metals

2.4.5 Non-Metals

2.4.6 Alkali Metals

2.4.7 Halogens

2.4.8 Oxides

2.4.9 End of Topic Test - The Periodic Table

2.5 Materials & the Earth

2.5.1 The Composition of The Earth

2.5.2 The Structure of the Earth

2.5.3 Igneous Rocks

2.5.4 Sedimentary Rocks

2.5.5 Metamorphic Rocks

2.5.6 The Rock Cycle

2.5.7 Physical Weathering

2.5.8 Chemical Weathering

2.5.9 Biological Weathering

2.5.10 The Formation of Fossils

2.5.11 Crude Oil

2.5.12 End of Topic Test - Earth

2.5.13 The Earth's Early Atmosphere

2.5.14 The Earth's Atmosphere Today

2.5.15 Oxygen in the Atmosphere

2.5.16 Carbon Dioxide in the Atmosphere

2.5.17 Greenhouse Gases

2.5.18 Climate Change

2.5.19 Resources

2.5.20 Recycling

2.5.21 Ceramics

2.5.22 Polymers

2.5.23 Composites

2.5.24 End of Topic Test - Materials

2.5.25 End of Topic Test - Polymers

2.6 Reactivity

2.6.2 Ionic Bonding

2.6.3 State Symbols

2.6.4 Balancing Chemical Equations

2.6.5 Relative Formula Mass

2.6.6 Calculating the Relative Formula Mass

2.6.7 The Reactivity Series

2.6.8 Carbon & The Reactivity Series

2.6.9 Displacement Reactions

2.6.10 Displacement Reactions - Halogens

2.6.11 Alloys

2.6.12 Metal Alloys

2.7 Energetics

2.7.1 Measuring Gas Production

2.7.2 Observing a Colour Change

2.7.3 Analysing Reaction Rates

2.7.4 Factors Affecting the Rate of Reaction

2.7.5 Catalysts

2.7.6 Testing for Oxygen

2.7.7 Energy Changes During Reactions

2.8 Properties of Materials

2.8.1 Testing for Gases

2.8.2 Alloys

2.8.3 Density

2.8.4 Density of Solids, Liquids & Gases HyperLearning

3.1.1 Energy Stores & Pathways

3.1.2 Energy Transfers

3.1.3 Common Energy Transfers

3.1.4 Wasted Energy

3.1.5 Efficiency of Energy Transfer

3.1.6 Sankey Diagrams

3.1.7 Heat & Temperature

3.1.8 Heat Transfer

3.1.9 Conductors vs Insulators

3.1.10 Reducing Energy Transfers

3.1.11 Energy & Power

3.1.12 Energy in Food

3.1.13 Calories

3.1.14 Food Labels

3.1.15 Energy at Home

3.1.16 Fuel Bills

3.1.17 Calculating Fuel Bills

3.1.18 Non-Renewable Energy - Fossil Fuels

3.1.19 Other Non-Renewables

3.1.20 Renewable Energy - Air & Ground

3.1.21 Renewable Energy - Water

3.1.22 End of Topic Test - Energy

3.2 Forces & Motion

3.2.1 Forces

3.2.2 Contact Forces

3.2.3 Balanced Forces

3.2.4 Force Diagrams & Resultant Forces

3.2.5 Free Body Diagram - Uses

3.2.6 Force & Acceleration

3.2.7 Gravity

3.2.8 Weight

3.2.9 Pressure

3.2.10 Speed

3.2.11 Relative Motion

3.2.12 Friction

3.2.13 Water & Air Resistance

3.2.14 Distance-Time Graphs

3.2.15 Moments

3.2.16 Levers

3.2.17 Work

3.2.18 Machines

3.2.19 Work & Machines

3.2.20 Elasticity

3.2.21 Elasticity - Hooke's Law

3.2.22 Density

3.2.23 Floating & Sinking

3.2.24 End of Topic Test - Forces & Motion

3.2.25 Vacuums

3.2.26 Thermal Energy & Conduction

3.2.27 Convection & Radiation

3.2.28 Evaporation

3.3.1 Waves

3.3.2 Types of Waves

3.3.3 Observing Waves

3.3.4 Wave Speed

3.3.5 Earthquakes

3.3.6 Sound Waves

3.3.7 Uses of Sound Waves

3.3.8 The Interactions of Sound with Different Mediums

3.3.9 Reflecting Sounds

3.3.10 The Speed of Sound

3.3.11 Measuring the Speed of Sound

3.3.12 The Hearing Range of Humans

3.3.13 The Human Ear

3.3.14 Light Waves

3.3.15 Reflection

3.3.16 Drawing a Reflected Image

3.3.17 Refraction

3.3.18 The Human Eye

3.3.19 The Eye as a Pinhole Camera

3.3.20 Lenses

3.3.21 Colour

3.3.22 Seeing Colour

3.3.23 Colours of Light

3.3.24 Drawing Waves

3.3.25 Wave Interactions

3.3.26 Comparing Sound & Light

3.3.27 End of Topic Test - Waves

3.3.28 End of Topic Test - Sound

3.4 Electricity & Magnetism

3.4.1 Circuit Symbols

3.4.2 Resistors & Diodes

3.4.3 Electric Current

3.4.4 Measuring Current

3.4.5 Potential Difference

3.4.6 Series Circuits

3.4.7 Parallel Circuits

3.4.8 Resistance

3.4.9 Charges

3.4.10 Static Electricity

3.4.11 Magnets

3.4.12 Magnetic Fields

3.4.13 The Earth's Field

3.4.14 Electromagnetism

3.4.15 Uses of Electromagnets

3.4.16 Strength of Magnetic Fields

3.4.17 Circuit Symbols HyperLearning

3.5.1 Physical Reactions

3.5.2 Changes of State

3.5.3 Particles

3.5.4 Density

3.5.5 Density & the Particle Model

3.5.6 The Equation for Density

3.5.7 Dissolving

3.5.8 Brownian Motion

3.5.9 Diffusion

3.5.10 Filtration

3.5.11 Solids

3.5.12 Liquids

3.5.13 Gases

3.5.14 Weight & Mass

3.5.15 Gravity

3.5.16 Gravitational Field Strength

3.5.17 Gravity in Space

3.5.18 Atmospheric Pressure

3.5.19 Liquid Pressure

3.5.20 End of Topic Test - Matter

3.6 Space Physics

3.6.1 The Sun

3.6.2 The Planets

3.6.3 Other Astronomical Bodies

3.6.4 The Milky Way

3.6.5 Beyond The Milky Way

3.6.6 The Seasons

3.6.7 Days, Months & Years

3.6.8 The Moon

3.6.9 Light Years

3.6.10 End of Topic Test - Space

4 Thinking Scientifically

4.1 Models & Representations

4.1.1 Strengths & Limitations of Models

4.1.2 Symbols & Formulae to Represent Scientific Ideas

4.1.3 Analogies in Science

4.1.4 Changing Models – Atomic Theory

4.1.5 Working Safely in the Lab

4.1.6 Variables

4.1.7 Writing a Hypothesis & Prediction

4.1.8 Planning an Experiment

4.1.9 Maths Skills for Science

4.1.10 Drawing Scientific Apparatus

4.1.11 Observation & Measurement Skills

4.1.12 Types of Data

4.1.13 Graphs & Charts

4.1.14 Bias in Science

4.1.15 Conclude & Evaluate

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Planning an Experiment

What is a hypothesis?

No.  A hypothesis is sometimes described as an educated guess.  That's not the same thing as a guess and not really a good description of a hypothesis either.  Let's try working through an example.

If you put an ice cube on a plate and place it on the table, what will happen?  A very young child might guess that it will still be there in a couple of hours.  Most people would agree with the hypothesis that:

An ice cube will melt in less than 30 minutes.

You could put sit and watch the ice cube melt and think you've proved a hypothesis.  But you will have missed some important steps.

For a good science fair project you need to do quite a bit of research before any experimenting.  Start by finding some information about how and why water melts.  You could read a book, do a bit of Google searching, or even ask an expert.  For our example, you could learn about how temperature and air pressure can change the state of water.  Don't forget that elevation above sea level changes air pressure too.

Now, using all your research, try to restate that hypothesis.

An ice cube will melt in less than 30 minutes in a room at sea level with a temperature of 20C or 68F.

But wait a minute.  What is the ice made from?  What if the ice cube was made from salt water, or you sprinkled salt on a regular ice cube?  Time for some more research.  Would adding salt make a difference?  Turns out it does.  Would other chemicals change the melting time?

Using this new information, let's try that hypothesis again.

An ice cube made with tap water will melt in less than 30 minutes in a room at sea level with a temperature of 20C or 68F.

Does that seem like an educated guess?  No, it sounds like you are stating the obvious.

At this point, it is obvious only because of your research.  You haven't actually done the experiment.  Now it's time to run the experiment to support the hypothesis.

A hypothesis isn't an educated guess.  It is a tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.

Once you do the experiment and find out if it supports the hypothesis, it becomes part of scientific theory.

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• 1.1 Meaning
• 1.2 About Hypotheses
• 2.1 Meaning
• 2.2 About Hypotheses
• 2.3.1 Edexcel
• 3.1.1 The Power of Inference
• 3.1.2 The Dance of Variables
• 3.1.3 The Beauty of Falsifiability
• 3.2.1 The Hypothetical World of Quantum Physics
• 3.2.2 Hypotheses in the Age of Artificial Intelligence
• 3.3.1 Citizen Science and Crowd-Sourced Hypotheses
• 3.3.2 Hypotheses Beyond Earth
• 3.4 Conclusion

Key Stage 3

A hypothesis is an attempt to describe or explain something before an experiment has been performed.

About Hypotheses

Key stage 4, beyond the curriculum, unveiling the secrets of hypotheses.

In the world of science, hypotheses are like the starting points of grand adventures, leading to discoveries and understanding. Let's journey beyond the curriculum and explore the fascinating aspects of hypotheses that go beyond the basics.

The Power of Inference

A hypothesis isn't just a guess; it's a well-informed prediction based on careful observation and prior knowledge. Scientists use the power of inference to formulate hypotheses that guide their experiments. By doing so, they unlock the mysteries of the natural world.

The Dance of Variables

Hypotheses often involve variables, those elements that can change or be manipulated in an experiment. But did you know that there are different types of variables? Scientists distinguish between independent variables (the ones you change) and dependent variables (the ones you measure). This distinction is crucial for designing experiments that yield meaningful results.

The Beauty of Falsifiability

One of the most critical aspects of a hypothesis is its testability. A good hypothesis is falsifiable, meaning it can be proven wrong through experimentation. This concept safeguards the integrity of scientific research, preventing bias and encouraging rigorous investigation.

Beyond the Basics

The hypothetical world of quantum physics.

In the realm of quantum physics, hypotheses take on a mind-bending twist. Scientists explore the behavior of subatomic particles and phenomena that defy classical intuition. Concepts like superposition and entanglement challenge our understanding of reality and open doors to groundbreaking discoveries.

Hypotheses in the Age of Artificial Intelligence

As technology advances, hypotheses extend beyond the laboratory. Machine learning algorithms formulate hypotheses to predict outcomes, from diagnosing medical conditions to recommending your next Netflix binge. The fusion of data and hypotheses is transforming various industries.

The Future of Hypotheses

The world of hypotheses continues to evolve, driving scientific progress and innovation. Embrace the spirit of curiosity, and who knows, your own hypotheses may shape the future of science.

Citizen Science and Crowd-Sourced Hypotheses

Today, citizen scientists around the world contribute to scientific research. Platforms like Zooniverse enable anyone to participate in experiments and help scientists test their hypotheses. It's a collaborative approach to discovery.

Hypotheses Beyond Earth

Scientists explore hypotheses beyond our planet. Astrobiology, for instance, speculates about life on other celestial bodies. Could there be extraterrestrial hypotheses waiting to be tested?

Remember, a hypothesis is not just a concept in a textbook; it's a powerful tool for unraveling the mysteries of the universe. As you delve deeper into your scientific journey, keep the spirit of hypothesis testing alive—it's the path to new horizons and exciting discoveries.

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Writing a Hypothesis for Your Science Fair Project

What is a hypothesis.

Once a scientist has a scientific question she is interested in, the scientist reads up to find out what is already known on the topic. Then she uses that information to form a tentative answer to her scientific question. Sometimes people refer to the tentative answer as "an educated guess." Keep in mind, though, that the hypothesis also has to be testable since the next step is to do an experiment to determine whether or not the hypothesis is right!

A hypothesis leads to one or more predictions that can be tested by experimenting.

Predictions often take the shape of "If ____then ____" statements, but do not have to. Predictions should include both an independent variable (the factor you change in an experiment) and a dependent variable (the factor you observe or measure in an experiment). A single hypothesis can lead to multiple predictions, but generally, one or two predictions is enough to tackle for a science fair project.

Examples of Hypotheses and Predictions

What if my hypothesis is wrong.

What happens if, at the end of your science project, you look at the data you have collected and you realize it does not support your hypothesis? First, do not panic! The point of a science project is not to prove your hypothesis right. The point is to understand more about how the natural world works. Or, as it is sometimes put, to find out the scientific truth. When scientists do an experiment, they very often have data that shows their starting hypothesis was wrong. Why? Well, the natural world is complex—it takes a lot of experimenting to figure out how it works—and the more explanations you test, the closer you get to figuring out the truth. For scientists, disproving a hypothesis still means they gained important information, and they can use that information to make their next hypothesis even better. In a science fair setting, judges can be just as impressed by projects that start out with a faulty hypothesis; what matters more is whether you understood your science fair project, had a well-controlled experiment, and have ideas about what you would do next to improve your project if you had more time. You can read more about a science fair judge's view on disproving your hypothesis at Learn More About the Scientific Method .

It is worth noting, scientists never talk about their hypothesis being "right" or "wrong." Instead, they say that their data "supports" or "does not support" their hypothesis. This goes back to the point that nature is complex—so complex that it takes more than a single experiment to figure it all out because a single experiment could give you misleading data. For example, let us say that you hypothesize that earthworms do not exist in places that have very cold winters because it is too cold for them to survive. You then predict that you will find earthworms in the dirt in Florida, which has warm winters, but not Alaska, which has cold winters. When you go and dig a 3-foot by 3-foot-wide and 1-foot-deep hole in the dirt in those two states, you discover Floridian earthworms, but not Alaskan ones. So, was your hypothesis right? Well, your data "supported" your hypothesis, but your experiment did not cover that much ground. Can you really be sure there are no earthworms in Alaska? No. Which is why scientists only support (or not) their hypothesis with data, rather than proving them. And for the curious, yes there are earthworms in Alaska .

What Makes a Good Hypothesis?

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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

• nebular hypothesis
• planetesimal hypothesis
• null hypothesis
• counter - hypothesis
• Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

Cite this Entry

“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 8 Apr. 2024.

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Kids definition of hypothesis, medical definition, medical definition of hypothesis, more from merriam-webster on hypothesis.

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Hypotheses and Proofs

In this post

What is a hypothesis?

A hypothesis is basically a theory that somebody states that needs to be tested in order to see if it is true. Most of the time a hypothesis is a statement which someone claims is true and then a series of tests are made to see if the person is correct.

Hypothesis – a proposed true statement that acts as a starting point for further investigation.

Devising theories is how all scientists progress, not just mathematicians, and the evidence that is found must be collected and interpreted to see if it gives any light on the truth in the statement. Statistics can either prove or disprove a theory, which is why we need the evidence that we gather to be as close to the truth as possible: so that we can give an answer to the question with a high level of confidence.

Hypotheses are just the plural of a single hypothesis. A hypothesis is the first thing that someone must come up with when doing a test, as we must initially know what it is we wish to find out rather than blindly going into carrying out certain surveys and tests.

Some examples of hypotheses are shown below:

• Britain is colder than Spain
• A dog is faster than a cat
• Blondes have more fun
• The square of the hypotenuse of a triangle is equal to the sum of the squares of the other two sides

Obviously, some of these hypotheses are correct and others are not. Even though some may look wrong or right we still need to test the hypothesis either way to find out if it is true or false.

Some hypotheses may be easier to test than others, for example it is easy to test the last hypothesis above as this is very mathematical. However, when it comes to measuring something like ‘fun’ which is shown in the hypothesis ‘Blondes have more fun’ we will begin to struggle! How do you measure something like fun and in what units? This is why it is much easier to test certain hypotheses when compared with others.

Another way to come up with a hypothesis is by doing some ‘trial and error’ type testing. When finding data you may realise that there is in fact a pattern and then state this as a hypothesis of your findings. This pattern should then be tested using mathematical skills to test its authenticity. There is still a big difference between finding a pattern in something and finding that something will always happen no matter what. The pattern that is found at any point may just be a coincidence as it is much harder to prove something using mathematics rather than simply noticing a pattern. However, once something is proved with mathematics it is a very strong indication that the hypothesis is not only a guess but is scientific fact.

A hypothesis must always:

• Be a statement that needs to be proven or disproven, never a question
• Be applied to a certain population
• Be testable, otherwise the hypothesis is rather pointless as we can never know any information about it!

There are also two different types of hypothesis which are explained here:

An Experimental Hypothesis –  This is a statement which should state a difference between two things that should be tested. For example, ‘Cheetahs are faster than lions’.

A Null Hypothesis –  This kind of hypothesis does not say something is more than another, instead it states that they are the same. For example, ‘There is no difference between the number of late buses on Tuesday and on Wednesday’.

Subjects and samples

We have already talked in an earlier lesson of different types of samples and how these are formed, so we will not dwell for too long on this. The main thing to make sure of when choosing subjects for a test is to link them to the hypothesis that we are looking into. This will then give a much better data set that will be a lot more relevant to the questions we are asking. There is no point in us gathering data from people that live in Ireland if our original hypothesis states something about Scottish people, so we need to also make sure that the sample taken is as relevant to the hypothesis as possible. As with all samples that are taken, there should never be any bias towards one subject or another (unless we are using something like quota sampling as outlined in an earlier lesson). This will then mean that a random collection of subjects is taken into account and will mean that the information that is acquired will be more useful to the hypothesis that we wish to look at.

The experimental method

By treating the hypothesis and the data collection as an experiment, we should use as many scientific methods as possible to ensure that the data we are collecting is very accurate.

The most important and best way of doing this is the  control of variables . A variable is basically anything that can change in a situation, which means there are a lot in the vast majority as lots of different things can be altered. By keeping all variables the same and only changing the ones which we wish to test, we will get data that is as reliable as possible. However, if variables are changed that can affect an outcome we may end up getting false data.

For example, when testing ‘A cheetah is faster than a lion’ we could simply make the two animals run against each other and see which is quickest. However, if we allowed the cheetah to run on flat ground and made the lion run up hill, then the times would not be accurate to the truth as it is much harder to run up a slope than on flat ground. It is for this reason that any variables should be the same for all subjects.

The only variable that is mentioned in the hypothesis ‘A cheetah runs faster than a lion’ is the animal that runs. Therefore, this is called the  independent variable  and is the only thing that we wish to change between experiments as it is the thing we wish to  prove has an effect on other results.

A  dependent variable  is something that we wish to measure in experiments to see if there is an effect. This is the speed at which something runs in our example, as we are changing the animal and measuring the speed.

Independent variable – something that stands alone and is not changed by other variables in the experiment. This variable is changed by the person carrying out the investigation to see if it influences the dependent variables. This can also be seen as an input when an experiment is created.

Dependent variable – this variable is measured in an experiment to see if it changes when the independent variable is changed. These represent an output after the experiment is carried out.

Standardised instructions

Another thing that is essential to carrying out experiments is to give both of the participants the same instructions in what you wish them to do. Although this may seem a little picky, there will be a definite difference in how a subject performs if they are given clear and concise instructions as opposed to given misleading and rushed ones.

Turning data into information

Experiments are carried out to produce a set of data but this is not the end of the problem! We will then need to interpret and change this information into something that will tell us what we need to know. This means we need to turn data in the form of numbers into actual information that can be useful to our investigation. Figures that are found through experiments are first shown as ‘raw data’ before we can use different tables and charts to show the patterns that have been found in the surveys and experiments that have been carried out. Once all the data is collected and in tables we can move on to using these to find patterns.

Once a hypothesis has been stated, we can look to prove or disprove it. In mathematics, a proof is a little different to what people usually think. A mathematical proof must show that something is the case without any doubt. We do this by working through step-by-step to build a proof that shows the hypothesis as being either right or wrong. Each small step in the proof must be correct so that the entire thing cannot be argued.

Setting out a proof

Being able to write a proof does not mean that you must work any differently to how you would usually answer a question. It simply means that you must show that something is the case. Questions on proofs may ask you to ‘prove’, ‘verify’ or ‘check’ a statement.

When doing this you will need to first understand the hypothesis that has been stated. Look at the example below to see how we would go about writing a simple proof.

Prove that 81 is not a prime number.

Here we have a hypothesis that 81 is not prime. So, to prove this, we can try to find a factor of 81 that is not 1 as we know the definition of a prime number is that it is only divisible by itself and 1. Therefore, we could simply show that:

The fact that 81 divided by 9 gives us 9 proves the hypothesis that 81 is not prime.

A proof for a hypothesis does not have to be very complex – it simply has to show that a statement is either true or false. Doing this will use your problem-solving skills though, as you may need to think outside the box and ensure that all of the information that you have is fully understood.

Harder examples

Being able to prove something can be very challenging. It is true that some mathematical equations are still yet to be proved and many mathematicians work on solving extremely complex proofs every day.

When looking at harder examples of proofs you will need to find like terms in equations and then think about how you can work through the proof to get the desired result.

Here we need to use the left-hand side to get to the right-hand side in order to prove that they are equal. We can do this by expanding the brackets on the left and collecting the like terms:

We have now expanded the brackets and collected the like terms. It is now that we will need to look at our hypothesis again and try to make the above equation into the right-hand side by moving terms around. We can see from the right-hand side of our hypothesis that we have a double bracket and then 2 added to this so we can begin by bringing 2 out of the above:

So we have now worked through an entire proof from start to finish. Here it is again using only mathematics and no writing:

In the above we have shown that the hypothesis is true by working through step-by-step and rearranging the equation on the left to get the one on the right.

The step-by-step approach to proofs

To prove something is correct we have used a step-by-step approach so far. This method is a very good way to get from the left-hand side of an equation to the right-hand side through different steps. To do this we can use specific rules:

1) Try to multiply out brackets early on where possible.  This will help you to cancel out certain terms in order to simplify the equation.

3) Take small steps each time.  A proof is about working through a problem slowly so that it is easy to spot what has been done in each step. Do not take big leaps in your work such as multiplying out brackets and collecting like terms all at once. Remember that the person marking your paper needs to see your working, so it is good to work in small stages.

4) Go back and check your work.  Once you have finished your proof you can go back and check each individual stage. One of the good things about carrying out a proof is that you will know if a mistake has been made in your arithmetic because you will not be able to get to the final solution. If this happens, go back and check your working throughout.

Harder proofs

When working through a proof that is more difficult it can be quite tricky. Sometimes we may have to carry out a lot of different steps or even prove something using another piece of knowledge. For example, it might be that we are asked to prove that an expression will always be even or that it will always be positive.

In the above equation we have worked through to get an answer that is completely multiplied by 4. This must therefore be even as any number (whether even or odd) will be even when multiplied by 4.

In this example we have had to use our knowledge that anything multiplied by 4 must be even. This information was not included in the question but is something that we know from previous lessons. Some examples of information that you may need to know in order to solve more difficult proofs are:

Any number that is multiplied by an even number must be even

A number multiplied by an even number and then added to an odd number will be odd

Any number multiplied by a number will give an answer that is divisible by the same number (e.g. 3 n  must be divisible by 3)

Any number that is squared must be positive

Above we have come to an answer that is multiplied by 3. This means that the answer has to be divisible by 3 also.

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A statement that could be true, which might then be tested.

Example: Sam has a hypothesis that "large dogs are better at catching tennis balls than small dogs". We can test that hypothesis by having hundreds of different sized dogs try to catch tennis balls.

Sometimes the hypothesis won't be tested, it is simply a good explanation (which could be wrong). Conjecture is a better word for this.

Example: you notice the temperature drops just as the sun rises. Your hypothesis is that the sun warms the air high above you, which rises up and then cooler air comes from the sides.

Note: when someone says "I have a theory" they should say "I have a hypothesis", because in mathematics a theory is actually well proven.

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Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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General Education

Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including: 

• Defining the term “hypothesis” 
• Providing hypothesis examples 
• Giving you tips for how to write your own hypothesis

So let’s get started!

What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid. 

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method .  Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

• Observation
• Asking questions
• Forming a hypothesis
• Analyze the data
• Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables 

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables:  independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable. 

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets. 

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement! 

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad.  These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.  

The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life: 

• If I get enough sleep, I’ll be able to get more work done tomorrow.
• If the bus is on time, I can make it to my friend’s birthday party. 
• If I study every night this week, I’ll get a better grade on my exam. 

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades). 

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say: 

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.” 

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis! 

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship. 

4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think. 

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than  twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against  science, as well. Take this hypothesis example: 

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.” 

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible. 

Good hypotheses ensure that you can observe the results. 

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable. 

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability 

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come  and how many leave. You also write down the temperature on the hour. 

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like: 

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment. 

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this: 

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while: 

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again! 

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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Activity: Hypothesis stories

This short activity quickly engages students in the process of science. They develop multiple hypotheses to explain a set of observations and figure out how to test these hypotheses.

• Key Stage: KS3
• Time required: 10-15 minutes

About this resource

• Resource type: classroom activity
• Theme: Working scientifically

Learning outcomes

• students pose multiple hypotheses to explain a set of observations
• students suggest methods to test their hypotheses
• students understand that scientific methods and theories developed as earlier explanations are modified to take account of new evidence and ideas

Curriculum links

Working scientifically skills.

Experimental skills and investigations

• ask questions and develop a line of enquiry based on observations of the real world, alongside prior knowledge and experience
• make predictions using scientific knowledge and understanding

Scientific attitudes

• understand that scientific methods and theories develop as earlier explanations are modified to take account of new evidence and ideas, together with the importance of publishing results and peer review

Analysis and evaluation

• present reasoned explanations, including explaining data in relation to predictions and hypotheses
• identify further questions arising from their results

Third Level Scientific Skills

Inquiry and Investigative Skills:

Plans and designs scientific investigations and enquiries:

• Demonstrates initiative and increasing independence in identifying a number of key questions and in formulating aims, predictions and hypotheses based on information, observations and knowledge.
• Designs procedures to test a hypothesis and identifies the independent, dependent and controlled variables, with limited assistance.

Analyses, interprets and evaluates scientific findings:

• Selects appropriate methods to record data/information and demonstrates increased precision in use of terminology, units and scales.
• Interprets and analyses data and information to establish relationships between the independent and dependent variables and links to the original hypothesis.
• Establishes links between the findings, aim and hypothesis.
• Relates findings to scientific knowledge and understanding.
• Draws a conclusion based on results gathered and in relation to the aim.
• Begins to consider alternative explanations and applies or extends conclusions to new situations or to identify further studies.
• Evaluates a range of aspects of the inquiry/investigation, including the relevance and reliability of evidence, and suggests at least two ways of improving the methodology, if repeated.

Presents scientific findings:

• Communicates effectively in a range of ways, for example, orally and through scientific report writing.
• Provides supporting evidence and quotes and acknowledges sources with limited assistance

Northern Ireland

Curriculum subject links.

• Overarching themes of Science, Technology and Design

Curriculum Skill Links

• Listen to and take part in discussions, explanations, role-plays and presentations
• Contribute comments, ask questions and respond to others’ points of view
• Communicate information, ideas, opinions, feelings and imaginings, using an expanding vocabulary
• Thinking, Problem-Solving and Decision-Making
• Develop creative and critical thinking in their approach to solving scientific problems
• Show deeper scientific understanding by thinking critically and flexibly, solving problems and making informed decisions, using
• Mathematics and ICT where appropriate
• Work effectively with others

The Microverse

Discover microscopic life in urban environments using DNA technologies. For secondary schools.

Browse all our Explore: Urban Nature resources

Use our learning resources with your students to explore the nature on your doorstep and discover the challenges it faces.

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• A UN Climate Change Conference (COP26) scrapbook

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The Hypothesis Box - thinking about science

• Ages 3-5 (EYFS)
• Ages 5-7 (KS1)
• Ages 7-11 (KS2)
• Ages 11-14 (KS3)
• Ages 14-16 (KS4)
• Ages 16-18 (KS5)
• Epistemology
• Language and Meaning
• Metaphysics

Taken from Peter Worley's book '40 Lessons to Get Children Thinking', Bloomsbury September 2015

Equipment needed and preparation:.

• An enclosed non-transparent box,
• A ball (optional - see below)

Starting age: 10 years

Key concept / vocabulary: Hypothesis, test, show, demonstrate, true, false, knowledge

Subject links: Science, RE and Philosophy

Key controversies: How is philosophy related to science? Can religious belief be treated in a similar way to scientific belief or are the two realms of belief disanalagous?

There are two possible outcomes: if the result confirms the hypothesis, then you’ve made a measurement. If the result is contrary to the hypothesis, then you’ve made a discovery.

Enrico Fermi, Italian physicist

Science is such that, when we get it wrong, reality answers back and tells us.

Rebecca Goldstein Newberger

Critical thinking tool: Falsification - this is when someone tries not to prove a theory or hypothesis but to disprove it. For instance, if the hypothesis is ‘all birds fly’ then the best course of action when testing the hypothesis is not to look for examples that confirm that hypothesis but to seek out examples that would disconfirm it. If someone were to look only for examples of birds that fly, thereby confirming the hypothesis, then they would be falling foul of the fallacy of seeking only to confirm , sometimes known as confirmation bias . No amount of examples of birds that fly would truly prove the hypothesis; only one example, however, of a bird that does not fly would utterly refute it. This is known as falsification and is associated with the Austrian-British philosopher Karl Popper (1902-1994).

Key facilitation tool: Counter-examples - when children make claims, especially general claims then a good thing to have the class do is search for a counter-example to the claim. For instance, if someone says, ‘Everything is possible,’ then, if the class has not already begun to do so, ask, ‘Can anyone think of an example of something that is not possible?’

Session Plan:

The main aim of this session is to explore the conditions necessary for showing a hypothesis to be true. No tests are performed and no experiments are constructed other than in the minds of the students. It is a reasoning exercise about what outcomes would be expected when X or Y is done and about what outcomes would show the hypothesis to be true. This kind of enquiry would be an excellent way to get a class to prepare for constructing tests and experiments in science and to consider what variables matter in relation to the hypothesis. This exercise also shows the links between science and philosophy - philosophy being reason-based and science being distinguished by being experimental and empirical as well as reason-based. You can see the close link in the example below because in thinking about the necessary conditions one needs to have a clear understanding of the concept ‘object’. This is where the conceptual analysis aspect of philosophy has a clear and important role in scientific reasoning.

Part one: The Object Hypothesis

Do: Before the session, and while the children are not there to see, put an item in a box such as a ball. Ask the class if anyone knows what a hypothesis is. Write up the word ‘hypothesis’ and do a concept map around it. Once this is done provide the class with a definition. Here is the dictionary definition:

* Hypothesis: a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation. 

Etymology: ‘hypothesis’ comes from the ancient Greek for ‘foundation’ and later went on to mean ‘to suppose’.

For a younger class here’s a simpler definition:

* A hypothesis is when you suppose something to be true before you know whether it is or not so that you can test it to see if it’s true.

Write the following hypothesis up on the board:

Hypothesis: There is an object in the box.

Task Question: How can we find out whether the hypothesis is true or false?

Someone is likely to say, ‘Open it.’ If they do, then this is how to respond (The structure of your questioning should follow - more or less - this example throughout this session):

Fac: If you open the box then what (outcomes) would you expect? (Eliciting expectations) Pupil: You might see an object or you might not. Fac: If you open it and you see an object then have you shown the hypothesis to be true or false? (Iffing and anchoring) Pupil: True. Fac: Can you say why? (Opening up - justification) Pupil: Because if there’s something there then… [the student continues] Fac: If you open it and you don’t see an object in it, then have you shown the hypothesis to be true or false?  Pupil: That depends. Fac: What would it depend on? Pupil: What an object is. Because if a germ or bacteria is an object then it would be true but if we mean something like…

The questioning strategies at the heart of this session are iffing, anchoring and opening up and - a new strategy - eliciting expectations . This is where you ask the pupil to say what outcomes they would need in order to show that what they are saying is true or, to put it as you will say it in this session: to show the hypothesis to be true . It is asking them to say what conditions are needed. In normal English, something like: ‘So what do you need to be able to show that?’

The Un-openable Box

You could make this task harder by making the following stipulation: ‘If you could not open the box (for whatever reason) then how would you be able to find out if the hypothesis is true?’

• shake the box.
• weigh the box.
• X-ray… and so on…

After each of these or other suggestions follow a similar structure to the ‘object hypothesis’ example above:

• If you shake the box what would you expect?
• If something rattles inside then would you have shown the hypothesis to be true or false?
• If something does not rattle inside then would you have shown the hypothesis to be true or false? And so on…

Extension activities:

More hypotheses suggestions

• There is an apple in the box.
• All birds fly.
• Teddy bears come alive when no one is watching.
• CO2 is the same as air.
• Water and ice weigh the same.
• Unicorns exist.
• The theory of abiogenesis is true (research ‘abiogenesis’ or the theory of ‘spontaneous generation’, associated with Aristotle, and also research Francesco Redi’s famous experiments (1668) to test this hypothesis. Interestingly, the jury’s still out on abiogenesis when it comes to the origins of life itself!)

Remember: do not perform the test or touch the box; explore, using the above questioning structure how they would test the hypothesis. As a science follow-up, you could try to perform the test that was thought-up in the session.

Open the box?

You may decide, at the end of the session, to open the box and reveal what is inside. However, there is another enquiry opportunity here about the nature and relationship of philosophy to science: you could ask the following two-part question:

• If this is a philosophy session then do we need to - and should we - open the box?
• If this were a science session do we need to - and should we - open the box?

Nested Questions:

• What are the similarities, if any, between philosophy and science?
• What are the differences, if any, between philosophy and science?

The students’ responses to this can reveal two things: their understanding of the subjects of philosophy and science, but also their intellectual/philosophical maturity. There may be those in the class, sensitive to the intellectual value of not revealing what is inside the box. Those that respond this way demonstrate, in my view, a sophisticated intellectual maturity.

The God Hypothesis

With older groups ‘The Hypothesis Box’ session affords a great opportunity to explore another of the big questions in philosophy: the question of God’s existence. Do ‘The God Hypothesis’ after running the hypothesis session above so that the two contrast.

Do: Write up the following hypothesis:

Hypothesis: God exists.

Task Question: How, if at all, can we find out if the hypotheses is true?

Nested questions.

• Is ‘the God hypothesis’ analogous to ‘the object/apple hypothesis’? (Are they the same kind of thing?)
• What counts as evidence with the ball example and what counts as evidence with the God example?
• Is evidence necessary for faith?
• Even if you think there is no evidence for God are there any good reasons for believing in God?
• What is it to know God?
• What is it to know that God exists?

Related Resources

The Philosophy Shop: Epistemology: Knowledge (section), Once Upon an If: Flat Earth, The Island

Download The Hypothesis Box - thinking about science

Ages: Ages 14-16 (KS4) , Ages 11-14 (KS3)

Subjects: Science , RE

Themes: Truth & Falsity , Reasoning , Hypothesis

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Conclude and evaluate

Part of Biology Working scientifically

• A conclusion sums up what has been found out during an investigation.
• A conclusion should be clearly structured and explained using scientific knowledge.
• At the end of an investigation, evaluate the results and method to judge how reliable the conclusion is.

What do you analyse to draw a conclusion in science?

Show answer Hide answer

Information or data.

Watch this video about how to draw conclusions from information and evaluate experiments.

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While you are watching, check how patterns in the data from the experiments are linked to the conclusion

Video Transcript Video Transcript

Presenter 2: We have been investigating how the height from which you drop a single ball affects how high it bounces.

Presenter 1: We will also use the results to write a conclusion and evaluate the experiment. What do your results show?

Presenter 2: The line of best fit shows that as you increase the height from which you dropped the ball, then the bounce gets higher also.

Presenter 1: As the independent variable on the x axis increases, so does the dependent variable on the y axis.

Presenter 2: A conclusion sums up what has been found in our investigation. So we can conclude that the greater the height from which you drop a ball, the higher it bounces.

Presenter 1: So, why does this happen then?

Presenter 2: Think about an elastic band. The more energy you use to pull the elastic band back, the further it will travel when you let it go.

Presenter 1: Oh, I see! The higher you drop the ball, the more energy it has when it hits the ground.

Presenter 2: So, the more energy it will have to bounce back up.

Presenter 1: In evaluating this experiment, we need to look at our method and results. When we look at our method, we check that we changed only one variable, measured another one and kept all the rest the same.

Presenter 2: So, we changed the height of the ball drop, which is the independent variable. We measured the height it bounced, which is the dependent variable. We kept all others the same - we controlled them. These include the type of ball and the floor that we dropped it on.

We filmed it so we could slow it down and read the measurement more accurately. Because we did all this, we know we have a valid experiment. When we look at our results we can ask ourselves these questions.

Are the readings a long way from the others? In other words, are there outliers?

And what is the spread of our results?

Presenter 1: To interpret what our results mean, we need to identify any patternsin our data by looking at our graph. We'll try the same experiment,but with a different type of ball.

Presenter 2: Now we can conclude that the greater the height you drop the ball and the type of ball you use, the more energy it will have and the higher it will bounce.

Presenter 1: We have used our knowledge to interpret our results. Then we wrote a conclusion and evaluated our method.

Interpreting data

Step 1 - Data interpretation

A good conclusion describes the relationship between variables, interpreted from a table of data, a graph or a chart.

Step 2 - Experiment carried out

An experiment was carried out to model the concept of erosion. Sugar cubes were shaken in a container and weighed every 20 seconds to see how the mass had changed. Any small parts of the cubes that had broken off during the shaking were removed before the mass was measured.

Step 3 - Results interpretation

Results from the sugar cube experiment would be recorded in a table. Results would show that the longer the sugar cubes were shaken for, the less their mass was. A good conclusion using this information would be: ‘the results show that the mass of the sugar cubes decreased as they were shaken for longer. The conclusion supports the hypothesis because it shows that erosion wears away material over time.'

Step 4 - Data presentation

The results from the experiment can also be shown using a graph, helping to spot patterns in the results. The conclusion would be the same as the one made from the table.

Step 5 - Using scientific knowledge

To make a conclusion better, scientific knowledge should be used to explain the findings. Sometimes using the information from the table or graph is good too. For example, from the sugar cube experiment, the amount of mass lost every 20 secs could be written down .

In the experiment modelling erosion, which was the dependent variable?

Evaluating evidence

More on Working scientifically

Find out more by working through a topic

Bias in science

• count 11 of 11

• count 1 of 11

• count 2 of 11

Writing a hypothesis and prediction

• count 3 of 11

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Lesson Plan: KS3 science – introducing practicals

• Subject: Maths and Science
• Date Posted: 27 September 2013
• View page as PDF: Download Now

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​Introduce your new Y7s to the thrilling world of scientific experimentation, with the help of Dr Joanna Rhodes inspiring suggestions…

​PRACTICAL MAGIC

Introduce your new Y7s to the thrilling world of scientific experimentation, with the help of Dr Joanna Rhodes inspiring suggestions…

TODAY YOU WILL…

+ LEARN ABOUT THE EXCITEMENT AND ROLE OF EXPERIMENTATION IN SCIENCE

+ LEARN HOW TO CARRY OUT EXPERIMENTS SAFELY AND ANALYSE AND PRESENT THE RESULTS

In walk my year 7 class. Full of excitement and energy, their first question is “Are we doing a practical today Miss?” Over the next few years as they move up through the school the question never changes. This plan is dedicated to turning your students into skilled scientists and experimenters. The focus is not simply on how to do practical work but how to use it for both discovery and verification of scientific facts and information. Used well, experiments can support the curriculum and lead to a deeper more sophisticated understanding that helps students to apply their knowledge.

In this lesson, students will start to understand the excitement of experimentation and the role of experiments in discovering and verifying scientific information. They will learn how to carry our experiments safely and how to obtain information from the experiment that supports or refutes a hypothesis. Pupils will learn about techniques to analyse information such as creating tables and plotting graphs and how to use computer equipment such as a data logger. Cross-curricular links are developed with other practical subjects and also history and English as we look at significant scientific discoveries and how modern discoveries are published and subjected to peer review.

STARTER ACTIVITY

ARE WE DOING A PRACTICAL TODAY?

Before students come into the laboratory set it out with stations containing a range of equipment that they will use over the year.

Good stations to use include a microscope and slides; Bunsen burner and metal salts for flame tests; power pack and leads with a bulb and resistor; measuring equipment with measuring cylinders, volumetric flasks, pipettes and a balance; and a clamp stand, spring and slotted masses. Before students begin to handle the equipment ask them to go to each station and carry out a mini risk assessment based on what they can see. It helps to encourage them to think of ‘Hazard, Risk, Precaution’: what could harm me, how could it harm me, what steps will I take to protect myself?

Allow students to feed back to each other in groups. Use the information generated to create some rules for the lab. Students will be more likely to buy into these having created them. Students then explore the laboratory in groups with a mini experiment to do at each station.

The activity allows students to become familiar with a range of equipment and it will also give them the excitement of anticipating some of the activities that they will be doing in future science lessons.

MAIN ACTIVITIES

MAKING DISCOVERIES

In this activity students investigate some major scientific discoveries. Ask them to log onto Factmonster [Additional Resource 1] and pick one of the summaries including: gravity; electricity; bacteria and health; evolution; the theory of relativity; the big bang theory; discovery of penicillin; and the structure of DNA. Students should then investigate their chosen theory, focusing on the experiments that scientists carried out. They should then produce a presentation. This could be a PowerPoint but encourage students to explore other ways of presenting, too, including acting out a short play of their own or using a scripted play from the ASE [AR2]; producing a Prezi [AR3] and delivering a TED style presentation [AR4]; or designing the front cover of a newspaper announcing the discovery with fabulous graphics from Make the Front Page [AR5].

TESTING A HYPOTHESIS

In this activity students come up with ways to test their own hypothesis. Examples include simple relationships between the height a ball is dropped from and the height it rebounds to; the size of nettle leaves growing in the sun or in shade; and the resistance of a light bulb and the current passing through it. Initially students should investigate what makes a good hypothesis, an example of how to do this can be found at Science Kids at Home [AR6]. They should then design an experiment using a model you have provided which could be the superb worksheet produced by Holt, Rinehart and Winston [AR7]. Developing students’ scientific literacy is a vital process and introducing new vocabulary about the variables they will be testing is appropriate at this stage.

Students should become familiar with the terms independent, dependent and control variable and how these relate to both the measurements they will make and how they will make the experiment a fair test. Science Buddies has a website to help with an excellent range of examples and descriptions in language that students will find easy to understand [AR8].

HOME LEARNING

Pitching for a prac!

The Nuffield Foundation [AR12] in partnership with the Institute of Physics, Royal Society of Chemistry and the Society of Biology has produced sheets for practical work. Give students the web address and ask them to find a practical that inspires them. They should produce a 3-minute pitch for the practical of their choice. Students can then vote for their top three experiments to do in lesson time or as a science club activity. This develops students’ own sense of discovery as they can investigate experiments that fascinate them.

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KS3 Science Explained

Keystage 3 or KS3 begins when children leave primary school and enter into secondary education. It marks the beginning of the build up to GCSE studies. As such, students will learn and take lessons in a variety of subjects including science.

KS3 Science presents a fundamental shift from the science lessons that children will have in primary school. Much of the theory is replaced by genuine experiments complete with theory and a designed hypothesis.

As a core subject, science is taught in ability sets through KS3. however, regardless of which ability set child falls into, the curriculum will remain unchanged. The key difference is that higher sets will be working towards more advanced levels. At the same time, the lower sets will be offered more support that they do typically need.

KS3 stands for key stage 3 and will begin as children enter secondary school, ending at year 9. As such, most students in KS3 will be between the ages of 12 and 14.

What Does The KS3 Science Syllabus Include:

The syllabus includes all three main areas of science:

It builds on topics that children already studied through their years in primary school. As such, pupils will be exploring topics that they are familiar with but at a more advanced level. As noted, they will be working in laboratories and will often carry out experiments. The results of these experiments gain more of a focus too. Students will be shown how to record and analyse the results.

The aim here is to ensure that children can develop three areas of scientific learning such as:

• Understanding of evidence
• Communication
• Practical and enquiry skills

Over three years children will study a range of different topics including:

• Energy, electricity, and forces
• Chemical and material behaviour
• The environment, earth, and the universe
• Organisms, behaviour, and health

Since there is no formal plan, these subjects can be taught in any order and will be spread out over two of three years depending on the school. Each area also has a range of different subtopics that a child will be taught too. For instance, the environment, earth, and universe will include:

• Weathering of rocks
• Motions of the moon, planets, stars, and sun
• Changes within the environment and their causes

Organisms, behaviour, and health will cover topics like:

• Life processes
• Human reproduction
• Adolescence
• Healthy eating and the importance of exercise
• Food chains
• Variation in living things

How Will KS3 Science Be Assessed?

As of 2009, there are no national assessments that are established as part of the KS3 science curriculum. Due to this, teachers are given the freedom to arrange as many or as few tests as they like. As such, KS3 science could be entirely assessed based on the completion of coursework. Although, it’s common for schools to have at least a few tests through the school year and potentially one formal assessment. This is important to determine whether students are absorbing the information and developing the necessary skills in key areas.

KS3 Science Learning At Home

Students will typically be given science homework as part of the KS3 curriculum. Indeed, typically, it’s expected that pupils will complete a couple of hours of science homework each week ontop of the total 3 hours that are completed during school time.

As well as homework, schools will often recommend that parents increase their child’s learning in a variety of ways such as:

• Home setup experiments
• Tools such as a pH testing kit
• Using a telescope to look at the different planets

Aims Of KS3 Science

There are numerous aims and goals of KS3 science for the teacher and the pupil. First, it is important to understand the connection between KS3 science and GCSE Science. Ideas and concepts are developed in key stage 3 to ensure that they can be used proficiently in key stage 4.

In most cases, students will have been studying the sicences for eight or nine years by the time they begin the GCSE course. To reach their full potential, it is crucial that they have mastered fundamental ideas and skills.

Students can complete KS3 and gain the knowledge they need to move to KS4. However, it is allso important that they understand how to apply this knowledge effectively. The aim is to ensure that different principles and models can be connected with key concepts.

The subtopics listed above are some of the concepts that can be used to ensure that students have a full and deeper understanding of the larger topic areas that will be relevant through KS4 as well as GSCE Science.

An example of this would be when students learn about ‘speed.’ Students will be required to know things such as relative motion and acceleration. They will also be provided with skills like using formulas such as speed = distance/time. However, they will also need to apply this knowledge. An example could be creating time-distance graphs while labeling different changes that are present in motion. Students could also be asked to describe how the speed of an object can vary when it is measured by observers who are not moving. This is one of the ways it's possible to assess their knowledge and understanding at KS3 level.

Another goal of KS3 science will be to teach pupils how to work scientificalls and approach learning the correct way. This includes a variety of skills such as how to analyse scientific patterns. Again, this goes beyond learning the knowledge as pupils will also need to understand how to apply it in a variety of different areas and situations.

Throughout KS3 students will learn how to analyse scientific data, discuss the data that has been collected, draw the key conclusions, and present the data in a way that can be understood. They will also discover how to develop ideas, approach criticisms of their ideas from the data, and even justify the opinions that they have presented. These are just some of the elements included in KS3 that will ensure students learn how to work scientifically, asking the right questions, and gathering the necessary conclusions.

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• Scientific Methods

What is Hypothesis?

We have heard of many hypotheses which have led to great inventions in science. Assumptions that are made on the basis of some evidence are known as hypotheses. In this article, let us learn in detail about the hypothesis and the type of hypothesis with examples.

A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.

Characteristics of Hypothesis

Following are the characteristics of the hypothesis:

• The hypothesis should be clear and precise to consider it to be reliable.
• If the hypothesis is a relational hypothesis, then it should be stating the relationship between variables.
• The hypothesis must be specific and should have scope for conducting more tests.
• The way of explanation of the hypothesis must be very simple and it should also be understood that the simplicity of the hypothesis is not related to its significance.

Sources of Hypothesis

Following are the sources of hypothesis:

• The resemblance between the phenomenon.
• Observations from past studies, present-day experiences and from the competitors.
• Scientific theories.
• General patterns that influence the thinking process of people.

Types of Hypothesis

There are six forms of hypothesis and they are:

• Simple hypothesis
• Complex hypothesis
• Directional hypothesis
• Non-directional hypothesis
• Null hypothesis
• Associative and casual hypothesis

Simple Hypothesis

It shows a relationship between one dependent variable and a single independent variable. For example – If you eat more vegetables, you will lose weight faster. Here, eating more vegetables is an independent variable, while losing weight is the dependent variable.

Complex Hypothesis

It shows the relationship between two or more dependent variables and two or more independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin, and reduces the risk of many diseases such as heart disease.

Directional Hypothesis

It shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature. For example- children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal. This shows the effect and direction of the effect.

Non-directional Hypothesis

It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.

Null Hypothesis

It provides a statement which is contrary to the hypothesis. It’s a negative statement, and there is no relationship between independent and dependent variables. The symbol is denoted by “H O ”.

Associative and Causal Hypothesis

Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable. Whereas, the causal hypothesis proposes a cause and effect interaction between two or more variables.

Examples of Hypothesis

Following are the examples of hypotheses based on their types:

• Consumption of sugary drinks every day leads to obesity is an example of a simple hypothesis.
• All lilies have the same number of petals is an example of a null hypothesis.
• If a person gets 7 hours of sleep, then he will feel less fatigue than if he sleeps less. It is an example of a directional hypothesis.

Functions of Hypothesis

Following are the functions performed by the hypothesis:

• Hypothesis helps in making an observation and experiments possible.
• It becomes the start point for the investigation.
• Hypothesis helps in verifying the observations.
• It helps in directing the inquiries in the right direction.

How will Hypothesis help in the Scientific Method?

Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:

• Formation of question
• Doing background research
• Creation of hypothesis
• Designing an experiment
• Collection of data
• Result analysis
• Summarizing the experiment
• Communicating the results

Frequently Asked Questions – FAQs

What is hypothesis.

A hypothesis is an assumption made based on some evidence.

Give an example of simple hypothesis?

What are the types of hypothesis.

Types of hypothesis are:

• Associative and Casual hypothesis

State true or false: Hypothesis is the initial point of any investigation that translates the research questions into a prediction.

Define complex hypothesis..

A complex hypothesis shows the relationship between two or more dependent variables and two or more independent variables.

Put your understanding of this concept to test by answering a few MCQs. Click ‘Start Quiz’ to begin!

Select the correct answer and click on the “Finish” button Check your score and answers at the end of the quiz

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