can you summarize this: The comparison between the bivariate regression model from Q3 and the multiple regression model from Q4 shows that the multiple regression model is a better predictor of the outcome variable. This is indicated by the R2 values, which represent the proportion of the variance for the dependent variable that's explained by an independent variable. For Q3, the R2 value is 90.1%, while for Q4, it's 98.3%. Q3 uses only one predictor variable, Area, to predict the outcome of Netsales. On the other hand, Q4 uses four predictor variables - Adcost, Area, Competitor, and Storesize - to predict the outcome of Netsales. This increase in predictor variables in Q4 likely contributes to its higher R2 value and its better predictive performance