Refer to exhibit.

You are asked to write a report on how specific variables impact your clients sales using a data set provided to you by the client. The data includes 15 variables that the client views as directly related to sales, and you are restricted to these variables only.
After a preliminary analysis of the data, the following findings were made:
1. Multicollinearity is not an issue among the variables
2. Only three variablesA, B, and Chave significant correlation with sales
You build a linear regression model on the dependent variable of sales with the independent variables of A, B, and C. The results of the regression are seen in the exhibit.
You cannot request additional datA. what is a way that you could try to increase the R2 of the model without artificially inflating it?

A.
Create clusters based on the data and use them as model inputs

B.
Force all 15 variables into the model as independent variables

C.
Create interaction variables based only on variables A,B,and C

D.
Break variables A,B,and C into their own univariate models