Science isn't a pile of facts to memorise — it's a way of finding things out that anyone can use. When you wonder why something happens and then test your idea carefully, you're doing science. This lesson walks through the method scientists use, and the single most important idea in it: the fair test.
The steps of the method
The scientific method is a loop you go round. It starts with an observation — you notice something. That leads to a question — why does it happen? You then make a hypothesis, which is a testable guess at the answer. You design an experiment to test it, collect data, and draw a conclusion: did the results support your hypothesis or not?
Crucially, the loop never really ends. A conclusion leads to new questions, and other people repeat your experiment to check it. Science is self-correcting because results have to be repeatable — if only you can get them, they don't count.
The scientific method is a loop — each conclusion leads to new questions.
A hypothesis is a testable prediction
A good hypothesis isn't a wild guess or an opinion — it's a specific prediction you could actually check. 'Plants grow better with more light' is testable. 'Plants are happier in the sun' is not, because you can't measure a plant's happiness.
The best hypotheses are written so that a result could prove them wrong. That's a strength, not a weakness: an idea that no possible experiment could disprove isn't really science.
The fair test: variables
This is the heart of good experiments. To find out if one thing affects another, you change only that one thing and keep everything else the same. The thing you deliberately change is the independent variable. The thing you measure is the dependent variable. Everything you keep the same is a control variable.
If you change two things at once, you won't know which one caused the result — that's an unfair test. Keeping everything else constant is what makes an experiment trustworthy.
Worked example
You want to test whether more light makes bean plants grow taller. How do you set up a fair test?
Independent variable (what you change): the amount of light each plant gets.
Dependent variable (what you measure): the height of each plant after two weeks.
Control variables (kept the same): same type of plant, same pot and soil, same amount of water, same temperature.
Use several plants at each light level so one odd plant doesn't fool you.
Answer: Change only the light, measure the height, and keep everything else identical.
Data, and being honest
You record your results as data — often in a table, then a graph — and look for a pattern. A key habit: repeat readings and take an average, because a single measurement can be off. Never change your data to match what you hoped for; if the results don't support your hypothesis, that's a real and useful finding.
Finally, you draw a conclusion that the data actually supports, and you say what you're unsure about. 'The taller plants got more light' is a conclusion; 'light is the only thing that ever matters' is going too far beyond the evidence.
Check yourself
Try these. Pick an answer to see whether it's right and why.
What is a hypothesis?
A hypothesis is a specific, testable prediction — ideally one an experiment could prove wrong — not a proven fact or an opinion.
In an experiment, what is the independent variable?
The independent variable is the one thing you change on purpose; the dependent variable is what you measure in response.
Why do you keep control variables the same?
If more than one thing changes, you can't tell which caused the result. Keeping everything else the same makes it a fair test.
Your results don't support your hypothesis. What should you do?
A result that disproves a hypothesis is genuine, useful science. Changing data is never acceptable.
Why should other scientists be able to repeat your experiment?
Repeatable results are what make science trustworthy — if only one person can get a result, it can't be relied on.
In a nutshell
The method is a loop: observe, question, make a testable hypothesis, experiment, collect data, conclude — then start again.
A hypothesis is a specific prediction you could prove wrong, not an opinion.
A fair test changes one thing (the independent variable), measures the effect (the dependent variable), and keeps everything else the same.
Record data honestly, repeat readings, and only conclude what the evidence supports.
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