writing a hypothesis ks3

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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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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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved April 16, 2024, from https://www.scribbr.com/methodology/hypothesis/

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• Knowledge Base
• Methodology
• How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

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.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, 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 variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

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 identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise 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.

Step 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

Step 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.

Step 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 .

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.

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).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Cite this Scribbr article

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McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 15 April 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/

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• The Number System and Place Value
• Calculations and Numerical Methods
• Fractions, Decimals, Percentages, Ratio and Proportion
• Properties of Numbers
• Patterns, Sequences and Structure
• Algebraic expressions, equations and formulae
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Geometry and measure

• Angles, Polygons, and Geometrical Proof
• 3D Geometry, Shape and Space
• Measuring and calculating with units
• Transformations and constructions
• Pythagoras and Trigonometry
• Vectors and Matrices

Probability and statistics

• Handling, Processing and Representing Data
• Probability

Working mathematically

• Thinking mathematically
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For younger learners

• Early Years Foundation Stage

Advanced mathematics

• Decision Mathematics and Combinatorics
• Advanced Probability and Statistics

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

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Scientific methods teaching resources

Worksheets and ideas to get students thinking about the scientific method and how to write up a scientific investigation (key stage 3 and gcse)..

Please forgive the URL of this page – there is no scientific method, but rather a collection of diverse methods that scientists use to inquire about the world.

What is science?

What is science ? A practical demonstration that asks students: What is science? This simple but powerful demonstration asks students to generate and test their own hypotheses in a similar way to research scientists. ( PDF )

Writing up a scientific investigation: the Practical Planner!

Template for writing up a scientific investigation . This fantastic resource by Tom Kitwood provides a template and scaffold for students to use when planning and carrying out any scientific investigation. It is best to enlarge this document to fill an A3 page. ( PDF )

• Writing a scientific method

Worksheet to help students write a scientific method . Students write a method. Their partner carries out the experiment and provides feedback. The method is then re-written and improved. This resource was co-designed with Catherine O’Riordan.  ( PDF )

• Variables in science
• Reproducible and repeatable measurements

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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Writing a Scientific Method KS3

Subject: Physics

Age range: 11-14

Resource type: Lesson (complete)

Last updated

27 November 2019

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Power Point aimed at lower KS3 to learn how to write a Scientific Method for making a cup of tea.

Recommend trying out some of the methods that the students come up with, making sure you are following it word for word and overacting any mistakes or issues to highlight them.

It is important to discuss why each method you go through is good or bad and ask the students to tell you how it could be better. May even be a good idea to give them some more time to try to improve their method and attempt the cup of tea again.

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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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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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