ABSTRACT

The Pearson correlation coefficient determines the strength of the linear relationship between two variables. Simple linear regression assumes that both variables are interval- or ratio-scaled. In addition, the dependent variable should be normally distributed around the prediction line. This, of course, assumes that the variables are related to each other linearly. Typically, both variables should be normally distributed. Dichotomous variables are also acceptable as independent variables. Multiple linear regression assumes that all variables are interval- or ratio-scaled. In addition, the dependent variable should be normally distributed around the prediction line. This, of course, assumes that the variables are related to each other linearly. The Spearman correlation coefficient determines the strength of the relationship between two variables. It is a nonparametric procedure.