Commentary

analysis does not test for causal relationships, only whether there is a relationship and, to some extent, the strength of this relationship. Linear regression analysis is used to predict or estimate the value of a normally distributed response variable from the known values of one or more explanatory variables which are not necessarily normally distributed. When the analysis uses a single explanatory variable, the procedure is called simple regression; when it uses a combination of explanatory variables, it is called multiple regression. An estimated simple linear regression line is described by the equation for a line: Y = a + bX where Y = the value of the response variable to be predicted, a = the point at which the regression line crosses the Y axi