what multiple linear regression mlr can tell you
simple linear regression is a function that allows an analyst or statistician to make predictions about one variable based on the information that is known about another variable linear regression can only be used when one has two continuous variables an independent variable and a dependent variable the independent variable is the parameter that is used to calculate the dependent variable or outcome a multiple regression model extends to several explanatory variables the mlr model is based on the following assumptions mlr assumes there is a linear relationship between the dependent and independent variables that the independent variables are not highly correlated and that the variance of the residuals is constant 2the coefficient of determination r squared is a statistical metric that is used to measure how much of the variation in outcome can be explained by the variation in the independent variables r2 always increases as more predictors are added to the mlr model even though the predictors may not be related to the outcome variable r2 by itself can t thus be used to identify which predictors should be included in a model and which should be excluded r2 can only be between 0 and 1 where 0 indicates that the outcome cannot be predicted by any of the independent variables and 1 indicates that the outcome can be predicted without error from the independent variables 