ABSTRACT
Many aspects of multiple regression analysis are straightforward extensions of the methods used to analyze the simple linear regression model. There are several ways in which a multiple regression analysis differs from a simple linear regression. One is that interpreting the regression coefficients raises some important issues. This chapter discusses by One can interprets the regression function by considering the effect of each predictor on the response, or one can think of the relationship between the entire set of predictors and the response variable. It also discusses the very fact that there are several predictor variables leads to new issues that do not naturally arise with only a single predictor. One way to interpret the multiple regression models is to consider the relationship between Y and one of the predictor variables, holding the other predictor variables constant.
