Linear regression analysis

3. An experiment was conducted to examine the effect of drug dosage of a cholesterol lowering drug (X ) on reduction of cholesterol level (Y). A variable race/ethnicity (Z) with four levels (White, Black, Asian, and Hispanic) is also included. A linear regression model of Y on the main effects of X and Z is fitted. How many regression parameters are there in the model (including intercept)? (A) 3 (B) 4 (C) 5 (D) 64. (Continuation) Suppose the interaction effect of X and Z is also fitted in the above model and is found to be significant. We may conclude that (A) X and Z are important predictors of Y. (B) subjects of different races may require different dosage to achieve same reduction in cholesterol level. (C) interpreting the main effect of X on Y is not meaningful. (D) All of the above. 5. Following are partial SAS outputs obtained by fitting a multiple linear regression model of prostate cancer specific antigen (Y) on three variables - Cancer Volume, Degree of capsular pentration (Capsular), and Age of patient. Can we drop Capsular from a regression model containing Cancer Volume and Capsular only?Source DF Type I SS Mean Square F Value Pr > F CancerVolume 1 62202.34271 62202.34271 62.15 <.0001 capsular age source df type iii ss mean square f value pr> F CancerVolume 1 17924.28614 17924.28614 17.91 <.0001 capsular age standard parameter estimate error t value pr> It Intercept 9.683368319 28.08965523 0.34 0.7311 CancerVolume 2.406749572 0.56871460 4.23 <.0001 capsular age no because the appropriate p-value is yes>