Question: 5.15 For Table 2.6. we tted a logistic model. treating death penalty as the response (I = yes} and defendant's race (I = white} and

5.15 For Table 2.6. we tted a logistic model. treating death penalty as the response (I = yes} and defendant's race (I = white} and victims' race (1 = white) as indicator predictors. Table 5.16 shows results. a. Interpret parameter estimates. Which group is most likely to have the yes re aponse? Find the estimated probability in that case. it. Interpret 95% condence intervals for conditional odds ratios. c. Test the effect of defendant's race, controlling for victims' race, using a (i) Wald test and (ii) likelihood-ratio test. Interpret. d. Test the goodness of t of the model. Interpret. Table 5.16 Software Output (Based on SAS) for Exercise 5.15 on the Death Penalty Criteria For Assessing Goodness Of Fit: Criterion DF value Deviance 1 $3198 Pearson Chi-Square 1 o.1era Log Likelihood 209.4133 Standard Likelihood Ratio Parameter Estimate Error 55% Conf Limits Chiquuare Intercept 35961 b.5069 4JT54 2J349 5o.33 def o.ssrs c.3571 1.5633 o.114o 5.59 Vic 2.1id D.EGDE 1.363 3.?1?5 15.03 LR Statistics Source DF Chi-Square Pr :- ChiSq def 1 5.01 D.O251 via 1 2.35 .O1

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