The dependent variable is the variable that is being measured or tested in an experiment. 1 For example, in a study looking at how tutoring impacts test scores, the dependent variable would be the participants’ test scores, since that is what is being measured.

The two main methods of establishing ecological validity are veridicality and verisimilitude. Veridicality is the degree to which test scores correlate with measures of real-world functioning, and verisimilitude is the degree to which tasks performed during testing resemble those performed in daily life.

A main effect (also called a simple effect) is the effect of one independent variable on the dependent variable. It ignores the effects of any other independent variables (Krantz, 2019). In general, there is one main effect for each dependent variable.

For example, in the research on cigarette-smoking and lung cancer, cigarette-smoking, which has already been done by many subjects, is the independent variable.” (Kerlinger, 1986, p. 32) Lung cancer “depends” on smoking. Smoking “depends” on lung cancer.

A nominal variable is a categorical variable. Observations can take a value that is not able to be organized in a logical sequence. Examples of nominal categorical variables include sex, business type, eye colour, religion and brand.

An independent variable, sometimes called an experimental or predictor variable, is a variable that is being manipulated in an experiment in order to observe the effect on a dependent variable, sometimes called an outcome variable.

In multiple regression, the criterion is predicted by two or more variables.

The constant term in regression analysis is the value at which the regression line crosses the y-axis. The constant is also known as the y-intercept. Surprisingly, while the constant doesn’t usually have a meaning, it is almost always vital to include it in your regression models!