Describe the differences between independent and dependent variables.

Independent variables are manipulated in an experiment, while dependent variables are measured based on changes in the independent variables.

In more detail, independent and dependent variables are fundamental components of scientific experiments. The independent variable is the factor that the researcher intentionally manipulates or changes in order to observe its effect on the dependent variable. It is called 'independent' because its variation does not rely on any other variable in the experiment. For example, in a study investigating the effect of sleep on test performance, the amount of sleep is the independent variable. The researcher can control this by setting different sleep durations for participants.

On the other hand, the dependent variable is the outcome that the researcher measures. It 'depends' on the independent variable, and changes in response to the manipulation of the independent variable. In the aforementioned sleep study, the test performance would be the dependent variable. The researcher would measure this after manipulating the independent variable, to see if changes in sleep duration have an effect on test scores.

Understanding the difference between these two types of variables is crucial for designing and interpreting research in psychology. The independent variable provides the basis for experimental manipulation, allowing the researcher to establish cause-and-effect relationships. The dependent variable, meanwhile, provides the data that the researcher analyses to determine the effect of this manipulation.

In essence, the independent variable is the cause, and the dependent variable is the effect. The researcher manipulates the independent variable and then observes whether this leads to changes in the dependent variable. This allows them to draw conclusions about whether the independent variable has an effect on the dependent variable. However, it's important to remember that correlation does not necessarily imply causation, and other factors (known as confounding variables) may also influence the dependent variable.