Design Controlled Experiments and Run Fair Tests in Science

When you do a controlled experiment, you test one thing at a time to find out what causes a change. You keep everything else exactly the same so your results are fair and trustworthy. This is also called a fair test.

For example, if you want to know how much water affects plant growth, you give each plant a different amount of water but use the same soil, the same pot size, and the same amount of sunlight. That way, you know water is the only thing causing any difference you see.

A variable is anything in an experiment that can change or be measured. When you design a controlled experiment, you work with three kinds of variables.

The independent variable is the one thing you purposely change to test its effect. The dependent variable is what you measure or observe as a result it depends on what you changed. The controlled variables are all the other things you keep the same so they do not affect your results.

For example, if you test whether light color affects plant height, the light color is your independent variable, the plant height is your dependent variable, and the water amount and soil type are your controlled variables. You can build on this understanding when you explore Variable Control: Independent and Dependent Variables.

Every good science investigation follows a clear order. First, you ask a clear, testable question one that can be answered by doing an experiment and collecting measurable data. For example: "Does adding fertilizer make bean plants grow taller in two weeks?"

Next, you form a hypothesis an educated guess about what will happen, based on what you already know. Then you design your experiment, collect data, and write a conclusion. This order helps you stay organized and get reliable results.

You already practiced asking testable questions in Question Formation: Developing Testable Questions, and you learned to plan simple experiments in Investigation Design: Planning Simple Experiments. Those skills are the foundation for everything you do here.

A control group is the group in your experiment that does not receive the change you are testing. It stays unchanged so you have something to compare your results against.

For example, if you are testing whether fertilizer helps plants grow, the plants that receive no fertilizer are your control group. Without a control group, you cannot know whether the fertilizer really made a difference. The control group gives you a baseline a starting point for comparison.

Scientists repeat experiments more than once to make sure the results are reliable and not just by chance. If the same results appear every time, you can be more confident they are real.

One-time results could be caused by accidents or small errors. Repeating your experiment makes your findings stronger and more trustworthy. When you collect and record your data carefully, you can look for patterns a skill you will develop further in Data Analysis: Patterns and Relationships.

Variable: A variable is anything in an experiment that can change or be measured, such as temperature, amount of water, or plant height. You decide which variable to change, which to measure, and which to keep the same.

Fair test: A fair test is an experiment where you change only one variable at a time while keeping everything else the same. This makes your results trustworthy because you know exactly what caused any difference.

Independent variable: The independent variable is the one thing you purposely change in your experiment to see what effect it has. For example, if you change the amount of sunlight a plant gets, sunlight is your independent variable.

Dependent variable: The dependent variable is what you measure or observe as a result of your experiment. It "depends" on the independent variable. For example, how tall a plant grows is the dependent variable when you are testing sunlight.

Controlled variables: Controlled variables are all the things you keep the same in every group of your experiment so they do not affect your results. For example, using the same soil and pot size for every plant keeps those factors controlled.

Hypothesis: A hypothesis is an educated guess about what will happen in your experiment, made before you begin testing. It is based on what you already know or have observed, and you check it against your results at the end.

Control group: The control group is the group in your experiment that does not receive the independent variable. It gives you a standard to compare against so you can see whether your change made a real difference.

Observation: An observation is when you use your senses sight, hearing, touch, smell to notice and describe what is happening during your experiment. Careful observations help you collect accurate data.

Data: Data is the measurements and observations you collect during your experiment. Data includes numbers, counts, and descriptions that you record and use to draw your conclusion.

Conclusion: A conclusion is a statement you write after your experiment that explains what your results show. It tells whether your hypothesis was supported and summarizes what you learned.

Prediction: A prediction is what you think will happen before you run your experiment. It is similar to a hypothesis and is based on your prior knowledge or observations.

Experiment: An experiment is the planned procedure you follow to test your hypothesis. A good experiment has clear steps that anyone could follow to get the same results.

Result: A result is what actually happened in your experiment. You compare your results to your hypothesis to see whether your prediction was correct.

Testable question: A testable question is one that can be answered by doing an experiment and collecting measurable data. For example, "Does adding fertilizer make bean plants grow taller?" is a testable question.

Try designing your own fair test at home or in class. Pick one thing to change like the amount of water you give two plants and keep everything else exactly the same. Record your observations in a table or chart, just like you practiced in Data Recording: Tables, Charts, and Graphs.

After your experiment, write a conclusion that explains what your results show. Ask yourself: Did my results match my hypothesis? If not, think about why they were different unexpected results are still valuable in science! You can also use what you learn here when you work on Testing Solutions: Evaluating Effectiveness and Design Process: Identifying and Solving Problems.

You are ready for controlled experiments because you have already learned important skills. You know how to ask testable questions from Question Formation: Developing Testable Questions, and you have planned simple experiments in Investigation Design: Planning Simple Experiments. You also know how to use evidence to draw conclusions from Drawing Conclusions: Evidence-Based Reasoning.

After mastering controlled experiments, you will be ready for more advanced topics. You will explore Experimental Design: Multiple Variables and Controls, learn about Data Collection: Quantitative and Qualitative Data, and study Analysis Methods: Patterns, Trends, and Relationships. You will also use precise measuring skills from Measurement: Standard Units and Precision to make your experiments even more accurate.

Controlled experiments connect to many other science skills you are building. When you work on Variable Control: Independent and Dependent Variables, you go deeper into understanding exactly how to identify and manage the variables in your experiments.

As you collect data, you will use skills from Data Analysis: Patterns and Relationships to find patterns in your results and understand what they mean. Accurate measurement is also key Measurement: Standard Units and Precision helps you collect data you can trust.

Controlled experiments also support design and engineering work. You will use investigation skills when you tackle Problem Definition: Identifying Design Challenges, Solution Design: Creating and Testing Solutions, and Optimization: Improving Designs. All of these topics work together to make you a stronger scientific thinker.