In an experiment, variables are fundamental to understanding how different factors interact with each other. The two main types of variables are the independent variable and the dependent variable.
Independent Variable: This is the variable that the researcher changes or controls in the experiment. It is considered the cause in a cause-and-effect relationship. For instance, if you are testing how different amounts of sunlight affect plant growth, the amount of sunlight is the independent variable because it’s what you are changing to observe the effect on plant growth.
Dependent Variable: This variable is what you measure in the experiment, and it depends on the independent variable. It is considered the effect in the cause-and-effect relationship. In the previous example, the growth of the plant (measured in height or health) is the dependent variable because it is what you are observing as a result of changing the amount of sunlight.
To summarize, in any experiment, the independent variable is what you manipulate, while the dependent variable is what you measure. Understanding the distinction between these variables is crucial for analyzing the results of your experiment correctly.