Use a likelihood ratio test to test for the significance of the regression. Compute the observed value of the test statistic and give the p-value symbolically. O Dev - 29.753; p-value = P(x (2) > 29.753) O Dev - 25.699; p-value = P(x (1) > 25.699) O Dev = 29.753; p-value = P(x (37) > 29.753) O Dev - 55.452; p-value = P(x2 (39) > 55.452) O Dev - 55.452; p-value = P(x (2) > 55.452) O Dev - 25.699; p-value = P(x- (2) > 25.699)Compute the odds of suffering a second heart attack for those that completed the program divided by the the odds of suffering a second heart attack for those that did not complete the program. Interpret that odds ratio. 0 Estimated OR=15.39; Not completing the program increases the odds of getting a 2nd heart attach by 15.39%. 0 Estimated OR=2.733; Completing the program decreases the odds of getting a 2nd heart attach by 2.733%. 0 Estimated OR: 00650; Completing the program decreases the odds of getting a 2nd heart attach by 6.5%. 0 Estimated OR=0.0650; Completing the program decreases the odds of getting a 2nd heart attach by 93.5%. 0 Estimated OR=2.733; Completing the program decreases the odds of getting a 2nd heart attach by 1.733%. 0 Estimated OR=15.39; Not completing the program increases the odds of getting a 2nd heart attach by l439%. Consider a study of n = 40 patients. They all suffered a heart attack and have anger management issues. The dataframe has 3 variables: - ha2 Whether or not a patient had a second heart attack. If ha2 = 1, then the patient had a second heart attack; otherwise, haZ = O. This is the response variable. a treatment Whether or not the patient completed an anger control treatment program. 1 means the program was completed, else is is 0. 0 anxiety A continuous variable that scores the patient's anxiety level. A higher score denotes higher anxiety. We fit a logistic regression model with R. Here is a summary of the fit. > summaryimod) Call: g|m(formu|a = ha2 ~ treatment + anxiety, binomial(link=|ogit), data = heartattack) Coefficients: Estimate Std. Error 2 value Pr(>|z|) (Intercept) -6.38342 2.50468 -2.549 0.01082 * treatment -2.73309 1.00548 -2.718 0.00656 '* anxiety 0.13970 0.04819 2.899 0.00374 ** --- Signif. codes: 0 *** 0.001 M 0.01 * 0.05.0.1 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 55.452 on 39 degrees of freedom Residual deviance: 29.753 on 37 degrees of freedom AIC: 35.753 Estimate the probability of suffering a 2nd heart attack for someone with an anxiety of 70 and did not complete the anger management program