The Difference between Independent and Dependent Variables

Many times, one hears about a recently published story that links soda consumption to obesity or smoking to lung disease. There are many more examples that one can find announced in a major newspaper, a popular magazine, a journal, or even television news programs. One may also find this information reported on advertisements for various products, even household cleaning products. If, in the search for more information, one read the study itself, they may find terms like “dependent variable” or “independent variable”.

The terms independent variable and dependent variable in statistics is an important concept which a number of people have trouble understanding. The definitions of both variables are important when one wishes to interpret or even set up a statistical analysis. Always used in combination, the dependent and independent variables make up the information that is in a study, even if some of the variables are found to not be important. Together, there are many statistical analyses that can be performed using the selected variables.

The dependent variable is the variable whose value depends, to a degree, on the independent variable. The dependent variable is the outcome or event of interest within a study. This outcome could even be used as an independent variable in another analysis. There may be multiple dependent variables with respect to a particular study or analysis. These dependent variables may be the same or different, and they may be analyzed separately from each other, depending on the desires of the researcher. There are many examples of these variables, using biomedical studies as examples, include heart disease, lung disease, and cancer.

An independent variable, like its name says, is a variable that does not depend on any other variable. It may be used alone or with other independent variables. They usually are used as factors influencing a particular outcome event in statisical processes. Most often, there are several independent variables, and, sometimes, there are even dozens of independent variables. Independent variables may or may not provide information about an outcome, but discovering the exact relationship is the point of a study. Often, the independent variable is chosen because a research believes they may impact the outcome measure or measures of interest. Some commonly used independent variables in medical and social research include race, gender, education level, and age.

For an example, let’s consider a study relating heart disease to blood pressure, smoking status, and dietary intake. The dependent variable is the outcome, in this case heart disease. The independent variables are blood pressure, smoking status, and dietary intake. Individually, blood pressure, smoking status, and dietary intake provide information about heart disease. But it is when they are together that they may provide a better picture of the outcome.