Introduction

Every scientific investigation begins with a question.

Some questions can be answered by carrying out experiments or making observations. Other questions cannot be answered scientifically because they involve opinions, personal preferences, or beliefs.

Learning to ask good scientific questions is an important skill. A well-written question helps scientists plan fair investigations, collect useful evidence, and draw reliable conclusions.

Great scientific discoveries often begin with simple questions, such as:

• Why do plants grow toward light?
• What causes rainbows?
• How does temperature affect the rate of a chemical reaction?

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What Makes a Scientific Question?

A scientific question is one that can be answered by:

• making observations
• collecting evidence
• carrying out investigations or experiments

Scientific questions focus on the natural world.

Examples:

• Does fertilizer affect plant growth?
• How does temperature affect the solubility of sugar?
• Which material is the best thermal insulator?

These questions can all be investigated using evidence.

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Testable and Non-Testable Questions

Not every question can be investigated scientifically.

Testable Questions

A testable question can be answered by collecting evidence.

Examples:

• Does sunlight affect the growth of bean plants?
• How does the length of a pendulum affect its period?
• Which paper towel absorbs the most water?

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Non-Testable Questions

A non-testable question cannot be answered through scientific investigation.

Examples:

• Which colour is the most beautiful?
• Which pet is the best?
• Is chocolate the tastiest food?

These questions depend on opinions or personal preferences rather than evidence.

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Characteristics of a Good Scientific Question

A good scientific question is:

• Clear
• Specific
• Focused
• Testable
• Measurable

Good questions identify exactly what will be investigated.

For example:

Instead of asking:

"How do plants grow?"

Ask:

"How does the amount of sunlight affect the height of bean plants over three weeks?"

The second question is much more specific and easier to investigate.

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Variables in Scientific Questions

Most scientific investigations involve variables.

A variable is something that can change during an investigation.

There are three main types.

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Example

Question:

How does the amount of water affect the height of bean plants?

Independent variable:

Amount of water

Dependent variable:

Height of the plant

Controlled variables:

• Type of plant
• Soil
• Pot size
• Amount of sunlight
• Temperature

Identifying variables helps scientists design fair and reliable investigations.

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Refining Scientific Questions

Sometimes a question is too broad.

For example:

"How does exercise affect people?"

This is difficult to investigate.

It can be improved by making it more specific.

For example:

"How does 20 minutes of daily running affect the resting heart rate of teenagers after four weeks?"

The refined question clearly states:

• what is changing
• what is being measured
• who is being investigated
• the time period

This makes it much easier to design an investigation.

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Examples of Refining Questions

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Why Scientific Questions Matter

A well-designed scientific question helps scientists:

• plan investigations
• identify variables
• collect useful data
• draw valid conclusions
• communicate their research clearly

Without a clear question, an investigation may become confusing or produce unreliable results.

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Real-World Applications

Scientists ask investigable questions in many fields, including:

• Medicine
• Environmental science
• Engineering
• Agriculture
• Astronomy
• Physics
• Chemistry
• Biology

Every new scientific discovery begins with someone asking an interesting question.

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Worked Examples

Example 1

Is the following question testable?

Does sunlight affect the growth of plants?

Answer:

Yes.

The amount of sunlight can be changed, and plant growth can be measured.

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Example 2

Is the following question testable?

Which season is the nicest?

Answer:

No.

The answer depends on personal opinion.

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Example 3

Identify the independent variable.

Question:

How does temperature affect the rate at which sugar dissolves?

Answer:

Temperature

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Example 4

Identify the dependent variable.

Question:

How does the amount of fertilizer affect plant height?

Answer:

Plant height

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Example 5

Rewrite the question to make it more specific.

Original question:

How does exercise affect health?

Possible answer:

How does 30 minutes of cycling each day affect resting heart rate in teenagers after six weeks?

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Did You Know?

In 1928, Alexander Fleming noticed that bacteria were not growing near a type of mould in one of his laboratory dishes. Instead of ignoring this unusual observation, he asked a scientific question about it. His investigation led to the discovery of penicillin, the world's first widely used antibiotic, which has saved millions of lives.

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Key Terms

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Key Takeaways

• Every scientific investigation begins with a clear question.
• Scientific questions must be testable using evidence from observations or experiments.
• Testable questions differ from questions based on opinions or beliefs.
• Identifying independent, dependent, and controlled variables helps scientists design fair investigations.
• Refining broad questions into specific, focused questions improves the quality of scientific investigations.
• Asking good scientific questions is the first step toward making new scientific discoveries.

Introduction

Scientists often want to know whether one factor causes another to change. For example:

• Does more sunlight help plants grow taller?
• Does temperature affect how quickly sugar dissolves?
• Does the length of a pendulum affect how long it takes to swing?

To answer questions like these, scientists carry out fair tests.

A fair test changes only one variable at a time while keeping everything else the same. This allows scientists to determine whether the variable being tested is truly responsible for any observed changes.

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What Is a Variable?

A variable is anything that can change during an experiment.

Variables allow scientists to investigate how different factors affect the outcome of an investigation.

Most experiments involve three main types of variables:

• Independent variable
• Dependent variable
• Controlled variables

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Independent Variable

The independent variable is the factor that the scientist deliberately changes.

It is sometimes called the manipulated variable.

Example

Question:

How does the amount of sunlight affect plant growth?

Independent variable:

Amount of sunlight

This is the only factor that is intentionally changed.

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Dependent Variable

The dependent variable is the factor that is measured or observed.

It depends on the independent variable.

Example

Question:

How does the amount of sunlight affect plant growth?

Dependent variable:

Height of the plant

The scientist measures how much the plants grow.

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Controlled Variables

Controlled variables are all the factors that are kept the same throughout the experiment.

Keeping these variables constant ensures that any differences in the results are caused only by the independent variable.

For the plant experiment, controlled variables might include:

• Type of plant
• Soil
• Pot size
• Amount of water
• Temperature
• Length of the investigation

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Why Are Controlled Variables Important?

Controlled variables make the investigation fair.

Imagine comparing two plants if:

• one receives more sunlight,
• one receives more water,
• one is planted in different soil.

If one plant grows taller, we cannot tell which factor caused the difference.

By controlling everything except one variable, scientists can make reliable conclusions.

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What Is a Fair Test?

A fair test is an experiment in which:

• only one independent variable is changed,
• the dependent variable is measured,
• all other relevant variables are kept constant.

This allows scientists to investigate the effect of one factor at a time.

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Designing a Fair Test

Suppose we want to answer this question:

How does water temperature affect the time taken for sugar to dissolve?

Identify the variables.

Only the water temperature should change.

Everything else should remain the same.

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Fair and Unfair Experiments

Fair Experiment

Two identical toy cars roll down ramps.

The only difference is:

• Ramp height

Everything else is identical.

This is a fair test.

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Unfair Experiment

Two toy cars are compared.

One ramp is higher.

One car is heavier.

One ramp is rougher.

Several variables changed.

This is not a fair test because we cannot identify the cause of any differences.

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How Variables Affect Results

Changing the independent variable may cause the dependent variable to change.

For example:

By changing only one variable, scientists can identify cause-and-effect relationships.

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Improving the Reliability of a Fair Test

Scientists often improve investigations by:

• Repeating measurements several times.
• Calculating the average result.
• Using accurate measuring equipment.
• Recording results carefully.
• Controlling all important variables.

These steps increase confidence in the results.

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Real-World Applications

Fair tests are used in many fields, including:

• Medical research
• Agriculture
• Engineering
• Environmental science
• Product testing
• Pharmaceutical development
• Manufacturing
• Space exploration

Reliable scientific investigations depend on carefully controlling variables.

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Worked Examples

Example 1

Question:

How does the amount of fertilizer affect plant growth?

Identify the independent variable.

Answer:

Amount of fertilizer

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Example 2

Identify the dependent variable.

Question:

How does the amount of fertilizer affect plant growth?

Answer:

Plant growth (such as height or mass)

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Example 3

Give two controlled variables for the plant investigation.

Answer:

Possible answers include:

• Type of plant
• Amount of water
• Soil type
• Pot size
• Temperature

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Example 4

Why is the following experiment unfair?

One group of plants receives more sunlight, more water, and different fertilizer.

Answer:

More than one variable has changed, so it is impossible to know which factor caused the results.

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Example 5

Why should only one independent variable be changed?

Answer:

So that any change in the dependent variable can be attributed to that single factor, making the investigation a fair test.

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Did You Know?

Before new medicines can be approved, they undergo controlled clinical trials. Researchers compare groups of patients while carefully controlling variables such as dosage, age, and health conditions. This helps ensure that any differences in patient outcomes are caused by the medicine itself rather than by other factors.

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Key Terms

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Key Takeaways

• Variables are factors that can change during an experiment.
• The independent variable is deliberately changed.
• The dependent variable is measured or observed.
• Controlled variables are kept the same to ensure a fair test.
• A fair test changes only one independent variable at a time.
• Carefully controlling variables allows scientists to draw reliable conclusions about cause-and-effect relationships.

Introduction

Before scientists carry out an experiment, they usually have an idea about what they think will happen and why. This idea helps them plan their investigation and decide what evidence to collect.

Scientists express these ideas by writing hypotheses and making predictions.

Although these terms are often used together, they are not the same thing. A hypothesis explains why something might happen, while a prediction states what is expected to happen if the hypothesis is correct.

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What Is a Hypothesis?

A hypothesis is a testable explanation for an observation or a scientific question.

A good hypothesis is:

• Based on scientific knowledge.
• Testable through investigation.
• Supported by logical reasoning.
• Able to be shown as supported or not supported by evidence.

A hypothesis is not simply a guess.

It is an educated explanation based on what is already known.

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What Is a Prediction?

A prediction states what you think will happen during an investigation if the hypothesis is correct.

Predictions describe the expected outcome of an experiment.

Example:

Prediction:

Plants receiving more sunlight will grow taller than plants receiving less sunlight.

A prediction does not explain why the plants will grow taller—that is the role of the hypothesis.

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Hypothesis vs Prediction

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Writing a Good Hypothesis

Many hypotheses are written using an If... then... because... structure.

Example:

If bean plants receive more sunlight,

then they will grow taller,

because sunlight provides the energy needed for photosynthesis.

This format includes:

• the independent variable
• the expected outcome
• the scientific explanation

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Making Logical Predictions

Predictions should be based on:

• scientific knowledge
• previous observations
• evidence from earlier investigations

Example:

Question:

How does water temperature affect the time taken for sugar to dissolve?

Prediction:

Sugar will dissolve faster in hot water than in cold water.

This prediction is based on what we know about particle motion.

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Testing a Hypothesis

A hypothesis is tested by carrying out a fair experiment.

Scientists:

1. Plan the investigation.
2. Identify the variables.
3. Collect measurements.
4. Analyse the results.
5. Decide whether the evidence supports the hypothesis.

Importantly, scientists do not prove a hypothesis to be absolutely true. Instead, the evidence may support or not support it under the conditions tested.

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Revising a Hypothesis

Sometimes the results do not match the prediction.

This does not mean the experiment has failed.

Instead, scientists:

• examine their methods,
• analyse the evidence,
• consider alternative explanations,
• revise their hypothesis if necessary.

Improving explanations based on new evidence is a normal and important part of science.

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Example Investigation

Question

How does the amount of fertilizer affect the growth of tomato plants?

Hypothesis

If tomato plants receive more fertilizer, then they will grow taller because fertilizer supplies nutrients needed for growth.

Prediction

Plants given extra fertilizer will have a greater average height after four weeks.

Investigation

Plants are grown under identical conditions, except for the amount of fertilizer they receive.

Conclusion

The results are used to determine whether the evidence supports the hypothesis.

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Why Are Hypotheses Important?

Hypotheses help scientists to:

• focus their investigations,
• identify relevant variables,
• design experiments,
• interpret results,
• develop scientific understanding.

Without hypotheses, investigations would lack direction.

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Real-World Applications

Scientists use hypotheses and predictions in many areas, including:

• Medicine
• Agriculture
• Environmental science
• Engineering
• Astronomy
• Chemistry
• Biology
• Physics

Every major scientific discovery begins with questions that lead to hypotheses and predictions.

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Worked Examples

Example 1

Which statement is a hypothesis?

A. Plants will grow 5 cm taller.

B. Plants grow taller in sunlight because they can carry out more photosynthesis.

Answer:

B

It explains why the plants are expected to grow taller.

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Example 2

Which statement is a prediction?

Answer:

Plants placed in sunlight will grow taller than plants kept in darkness.

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Example 3

Complete the hypothesis.

If the temperature of the water increases,

then ____________________,

because ____________________.

Possible Answer:

...the sugar will dissolve more quickly,

because the water particles move faster and collide with the sugar more often.

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Example 4

What should a scientist do if the results do not support the hypothesis?

Answer:

Review the evidence, consider possible sources of error, and revise the hypothesis if necessary.

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Example 5

Why must a hypothesis be testable?

Answer:

Because scientists need to collect evidence through observations or experiments to determine whether the evidence supports the hypothesis.

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Did You Know?

In the 1800s, Louis Pasteur tested the hypothesis that microorganisms come from existing microorganisms rather than appearing spontaneously. His famous swan-neck flask experiment provided strong evidence against the idea of spontaneous generation and helped establish the foundations of modern microbiology.

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Key Terms

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Key Takeaways

• A hypothesis explains why something is expected to happen.
• A prediction states what is expected to happen if the hypothesis is correct.
• Good hypotheses are testable and based on scientific reasoning.
• Predictions should be logical and supported by existing evidence.
• Experiments provide evidence that may support or not support a hypothesis.
• Scientists revise hypotheses when new evidence becomes available, helping scientific knowledge become more accurate over time.