**Control group** in a science experiment is like a special group that helps us understand the effects of what we're testing. It's kept separate to make sure that changes we make don't mess up our results. This way, we can be more certain about what's really causing things to happen.

Does it help to fertilize or something we just believe?

Example
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Imagine you have a garden and you want to see if a new type of fertilizer makes your plants grow taller. To find out, you decide to do an experiment.

In your experiment, you have two groups of plants. One group gets the new fertilizer, and the other group doesn't get any fertilizer at all. The group that doesn't get any fertilizer is called the "control group."

Now, think of the control group as the standard or normal group. Since they don't get the new fertilizer, you can compare how the plants in this group grow naturally without any special treatment.

By having a control group, you can see if the changes in the group that got the new fertilizer are because of the fertilizer itself or if it's just how plants naturally grow. It helps scientists make sure that any differences they see are really because of what they're testing and not just random variations. So, the control group is like the baseline that helps us understand if something new really makes a difference.

Types
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There are two types of control groups: *positive* and *negative*.
The terms "positive control group" and "negative control group" refer to two different types of control groups used in experiments.

### Negative control group

This group is not expected to show any significant response or effect.
It helps to ensure that the experimental setup is not causing unexpected changes on its own.
It provides a baseline to compare with the experimental group, helping researchers confirm that any observed effects are due to the specific treatment being tested.
Example: In a medicine test, a negative control group might receive a placebo (a fake treatment with no active ingredients). If the placebo group shows no improvement, it suggests that any improvement in the actual treatment group is likely due to the treatment itself and not just the act of receiving any treatment.

### Positive control group

This group is expected to show a known and significant response.
It helps to 
validate that the experimental setup is capable of producing the expected effects.
It serves as a comparison to the experimental group, indicating whether the experimental treatment is performing as expected.

### Examples

In a medicine test, a positive control group might receive a well-established and effective medication. If this group responds positively, it ensures that the experimental setup is capable of detecting a treatment effect. It also provides a benchmark to compare the effectiveness of the new treatment.

Summary
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In summary, the terms "positive" and "negative" refer to the expected outcomes in these control groups. "Negative" means no significant effect is expected, while "positive" means a known and significant effect is anticipated. Both types of control groups help ensure the reliability and validity of experimental results.