Consider a regression with predictors of X1 and X2. The total sum of squares is known as T670. And. we consider the following three linear regression models, and partial information on the ts of the three models are given below. (1) (2] Model 1: X1 alone is a predictor Residual degrees of freedom: 9 3' Multiple R-squared: 0.309 Model 2: {X1, X2] are predictors Residual degrees of freedom: 3 3' Multiple Rsquared: [1873 Model 3: {X1, factor(Xg)) are predictors, where \"factor(]" has the same function as the command with the same name in R. Residual degrees of freedom: 7' 3' Multiple Iii-squared: 0.8?4 Do you think that a general linear Ftest can be done between Model 2 and Model 3? Give the reason to your answer. And, if your answer is ''YES", then give the test statistics and a distribution needed to use along with stating degrees of freedom exactly. As considering X2 as a categorical variable, one want to test the effect of X2 with including X1 in the model. Compute the test statistics along with a distribution needed to use along with stating degrees of freedom exactly