In scientific experiments, understanding the roles of different variables is crucial. Two key types of variables are controlled variables and dependent variables. Here’s a clear explanation of each:
Controlled Variables
Controlled variables, also known as constant variables, are the factors that are kept unchanged throughout the experiment. These variables are controlled to ensure that any changes in the dependent variable are solely due to the manipulation of the independent variable. For example, if you are testing the effect of light on plant growth, the amount of water and type of soil would be controlled variables.
Dependent Variables
Dependent variables are the outcomes that are measured in an experiment. They depend on the independent variable, which is the factor that the experimenter manipulates. In the plant growth example, the dependent variable would be the height of the plants, as it is expected to change based on the amount of light they receive.
Key Differences
- Role in the Experiment: Controlled variables remain constant, while dependent variables change in response to the independent variable.
- Purpose: Controlled variables ensure the experiment’s validity by isolating the effect of the independent variable. Dependent variables provide the data needed to draw conclusions.
- Measurement: Controlled variables are not measured; they are kept the same. Dependent variables are measured to observe the effect of the independent variable.
Understanding these differences helps in designing robust experiments and interpreting results accurately.