Final answer:
The independent variable is what is being manipulated or controlled in an experiment, whereas the dependent variable is what is being measured. Control variables are kept constant to confirm the effect of the independent variable. In correlational studies, variables are not classified as independent or dependent, but their association is analyzed with a correlation coefficient, not implying causation.
Step-by-step explanation:
Difference Between Independent and Dependent Variables
In an experimental study, the independent variable is the factor that is manipulated or controlled by the experimenter, and it is the only important difference between the experimental and control groups. On the other hand, the dependent variable is what the researcher measures to assess the effect of the independent variable. A classic example would be an experiment to determine how fertilizer affects plant growth. Here, the type of fertilizer used is the independent variable, and the plant growth is the dependent variable, which depends on the type of fertilizer.
Control Variables and Their Importance
Control variables are constants during an experiment. They are not the main focus of the investigation but are kept constant to ensure that the test results are as reliable as possible. Control variables are important because they eliminate alternate explanations of experimental results, which helps to isolate the effect of the independent variable on the dependent variable.
Variables in a Correlational Study
In a correlational study, the aim is not to manipulate any variables but to observe the relationship between them. The variables are not classified as independent or dependent. Instead, the researcher studies whether an association exists between variables and to what degree, using the correlation coefficient. However, it's important to remember that correlation does not equate to causation.