In psychology statistics, research studies which involve collecting *quantitative data* (any data that can be counted or rendered as numbers) usually require you to collect and store data on a data sheet about several variables. When you conduct your statistical analyses on this data, you need to know what role each variable played in your research design. Generally speaking, you classify variables in psychology statistics as independent variables, dependent variables or covariates.

## Independent variables

Independent variables are sometimes referred to as *predictor variables**.* Strictly speaking, an *independent variable** *is a variable that you manipulate so that you can study how the changes in the independent variable influence changes in other variables. In some cases, you refer to variables as independent variables even when you’re not directly manipulating them.. This type of independent variable is a *quasiindependent variable*.

## Dependent variables

Dependent variables are sometimes referred to as *outcome variables** *or *criterion variables**. *A *dependent variable** *is usually the variable that you expect to change when you manipulate the independent variable. In other words, the dependent variable is the variable that the independent variable affects. Therefore, the dependent variable is so called because its value depends on the value of the independent variable (at least in theory).

## Covariates

A *covariate** *is a broad term used for a variable in a research design that’s neither an independent nor a dependent variable. In some designs you use a covariate to take account of other factors that might influence the relationship between the independent and dependent variable. A good research design measures these variables so that you can account for their influence. Within this research design, these variables are *covariates*. Covariates can also exist in research designs where no independent or dependent variables exist.