Scientific control facts for kids

Imagine you have two groups of plants that are exactly the same. You give fertilizer to one group (the treatment group). The other group gets no fertilizer (the control group). If the fertilized plants grow differently, you can be pretty sure it's because of the fertilizer!

A scientific control is a special part of an experiment that helps scientists make sure their results are accurate. It's like a way to double-check everything. When you do an experiment, you want to see if one specific thing (called the independent variable) causes a change. A control helps you make sure that nothing else is causing the change you see. This makes your experiment's results much more trustworthy. Scientific controls are a key part of the scientific method, which is how scientists learn about the world.

What are Controlled Experiments?

Controls are super important because they help rule out other reasons for your experiment's results. They stop things like mistakes in the experiment or even a scientist's own hopes from messing up the findings. Many controls are unique to the type of experiment being done. For example, in some lab tests, special markers are used just to make sure the equipment is working right. Choosing and using the right controls can be tricky, but it's vital for getting good, reliable results.

Let's say a scientist gives a new artificial sweetener to 60 lab rats. Ten of them get sick. Is it the sweetener, or something else? Maybe the sweetener is mixed with a liquid, and that liquid is what's making them sick. To check this, the scientist would do the experiment twice:

• Once with the sweetener mixed in the liquid.
• Once with just the liquid, no sweetener.

This way, the scientist can see if the sickness comes from the sweetener, the liquid, or neither. Controls are often needed when it's hard to separate one factor from another. For instance, if you have to use a tractor to spread fertilizer, the tractor itself might affect the plants. A good control would be to drive the tractor over some plots of land without spreading fertilizer. This helps you see the effect of the tractor versus the fertilizer.

The most common types of controls are negative and positive controls. When both of these work as expected, it usually means the experiment is set up well. It shows that the experiment gives a "no" answer when it should, and a "yes" answer when it should. Other types of controls include "vehicle controls" (like the liquid in the sweetener example) and "sham controls" (like fake surgery).

What is a Negative Control?

A negative control is like a "no treatment" group. It helps you see what happens when you don't apply the thing you're testing.

Imagine you're testing a new medicine. You have a group that gets the medicine (the treatment group). The negative control group would get a placebo, which looks like the medicine but has no active ingredients (like a sugar pill).

• If both the medicine group and the placebo group show no improvement, it means the medicine probably didn't do anything.
• If both groups show improvement, it means something else is causing the improvement, not just the medicine. This could be the placebo effect, where people feel better just because they think they're getting medicine.

The goal is for the medicine group to show more improvement than the placebo group. If they show the same amount of improvement, the medicine isn't really working better than nothing.

What is a Positive Control?

Positive controls are used to make sure your experiment is working correctly and can actually detect a result. It's like having a known answer to check your work.

For example, if you're testing a new way to find a disease, you would compare it to a test that is already known to work. This well-known test is your positive control. You already know it should give a positive result for people who have the disease. If your new test doesn't match the results of the positive control, something might be wrong with your new test or how you're doing the experiment.

Another example is measuring an enzyme in a liquid. A positive control would be a sample with a known amount of that enzyme. You expect this sample to show a lot of enzyme activity. If it doesn't, you know there's a problem with your experiment.

If your positive control doesn't give the expected result, you might need to repeat the experiment. Sometimes, using several positive controls can help you compare results even more accurately.

Why is Randomization Important?

In randomization, the groups that get different treatments are chosen completely by chance. This doesn't mean the groups will be exactly the same, but it helps make sure any small differences between them are spread out evenly. This stops unfair advantages or disadvantages from affecting your results.

For example, if you're testing how different fertilizers affect crop yield (how much food a plant produces), the soil in different parts of a field might be different. To control for this, you would randomly decide which fertilizer goes on which section of land. This way, any natural differences in the soil won't unfairly favor one fertilizer over another.

What are Blind Experiments?

Blinding means keeping important information hidden during an experiment. This helps prevent people's expectations or hopes from changing the results.

For example, in a medical study, patients might not know if they are getting the real medicine or a placebo. If they knew, they might feel better just because they expect to (the placebo effect). Also, the researchers or doctors might accidentally influence the experiment if they know who is getting what. This is called the observer effect.

A "blind" can be put on anyone involved in the experiment: the people taking part, the scientists, the technicians, or even the people analyzing the data. Sometimes, a fake surgery (called sham surgery) is even done to keep patients from knowing if they had the real procedure.

Sometimes, people in a blind experiment figure out what treatment they are getting. This is called "unblinding." If this happens before the experiment is over, it can mess up the results because the bias that blinding was supposed to prevent comes back. Unblinding is common and should always be reported by scientists. Blinding is a very important tool in the scientific method, especially in medicine, where it's often considered essential for good research. A medical study that isn't blinded is called an "open trial."

See also

• False positives and false negatives
• Designed experiment
• Controlling for a variable
• James Lind helped cure scurvy using a controlled experiment. This is often called the first clinical trial.
• Wait list control group