1. Now, run a multiple linear regression on the same variables but now include your other factors of interest.

a) How many observations are used in this analysis? If different from the previous model, why do you believe that is? (2 pts)

b) Why is the Adjusted R² different than the R²? (2 pts)

c) Report the predicted value of self-reported number of days experiencing poor health for Males. How does it change? (2 pts)

d) Interpret the beta coefficient for AVEDRNK2. (2 pts)

e) Were there any variables which were significant in the first model that were no longer significant in the second? If any, which ones and why may this have happened? (4 pts)

The SAS System 16:16 Thursday, April 7, 2022 The REG Procedure Model: MODEL1 Dependent Variable: POORHLTH POOR PHYSICAL OR MENTAL HEALTH Number of Observations Read 15000 Number of Observations Use 2590 Number of Observations with Missing Values |11450 Analysis of Variance Sum of Mean Source DF Squares F Value Pr > F Mode 12 22299 1858.23784 1.22 0.2624 Error 3537 5387890 1523.29606 Corrected Total 3549 5410197 Root MSE 39.02943 R-Square 0.0041 Dependent Mean 55.67155 Adj R-Sq 0.0007 Coeff Var 70.10659 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > It Intercept Intercept 56 36497 3.43477 16.41