Here's why they're important:

* To isolate the effect of the independent variable: You want to see if changes in your independent variable (the one you're manipulating) are causing changes in the dependent variable (the one you're measuring). Keeping other factors constant eliminates any confusion about what's causing the results.

* To ensure reliable results: If you let other things change randomly, your results might be due to those other factors, not the independent variable. This makes your experiment less reliable.

Examples of controlled variables:

* Temperature: If you're testing the effect of fertilizer on plant growth, you'd want to keep the temperature constant.

* Light: If you're testing the effect of different types of music on plant growth, you'd want to keep the amount of light constant.

* Time: If you're testing the effect of different types of exercise on heart rate, you'd want to keep the duration of the exercise constant.

In summary:

Controlled variables are crucial for a well-designed experiment. By keeping them constant, you can be more confident that any changes in the dependent variable are due to the independent variable, leading to more reliable and meaningful results.