9.3. Categorical explanatory variables¶. Recall how we have dealt with categorical explanatory variables to this point: Excel: We used IF statements and other tricks to create n-1 new columns in the ...

Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

Figure 1: The results of multiple linear regression depend on the correlation of the predictors, as measured here by the Pearson correlation coefficient r (ref. 2). ( a ) Simulated values of ...

R 2 is a statistical measure of the goodness of fit of a linear regression model (from 0.00 to 1.00), also known as the coefficient of determination. In general, the higher the R 2 , the better ...