The output below is from a multiple linear regression of surface finish on cutting RPM and cutting bit type, where bit type is a categorical variable taking values A,B,C, or D. To run the regression, indicators have been generated for bit types B, C, and D, e.g., if the bit is of type B then the indicator for B will take value 1 and all others will take value 0. Based on the analysis - what is the expected surface finished when the RPMs equal 250 and the bit used is of type B (please round your answer to the closest 10th, i.e., the first decimal place) SUMMARY OUTPUT Regression Statistics Multiple R 0.994 R Square 0.989 Adjusted R Square 0.987 Standard Error 1.089 Observations 35 ANOVA df SS MS F Regression 4 3178 794 670 Significance F 0.000 Residual 30 36 1 Total 34 3213 Coefficients Standard Error tStat P-value Lower 95% Intercept 24.49 2.47 9.90 0.0000 RPM 0.10 0.01 9.40 0.0000 19.44 0.08 Upper 95% 29.55 0.12 Type B -13.31 0.49 -27.32 0.0000 -14.31 -12.32 Type C -20.49 0.49 -42.06 0.0000 -21.48 -19.49 Type D -26.04 0.60 -43.62 0.0000 -27.26 -24.82 Question 1 1 pts Multicollinearity only occurs in multiple regression when two or more of the independent variables are highly positively (but not negatively) correlated. True O False Question 2 1 pts The intercept in a model that includes categorical (indicator) variables can be interpreted as the intercept for the level that was left out (i.e., was coded as O by the indicator variables). True False