Question: Evaluate this relationship using the methods for a logistic regression analysis. Call: glm(formula = McCain_vote ~ partyid7.n, family = binomial(link = logit), data = nes)

Evaluate this relationship using the methods for a logistic regression analysis.

Call: glm(formula = McCain_vote ~ partyid7.n, family = binomial(link = "logit"), data = nes) Deviance Residuals: Min 1Q Median 3Q Max -2.4692 -0.3689 -0.2120 0.3118 2.7591 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.78393 0.17685 -21.40 <2e-16 *** partyid7.n 1.13063 0.05236 21.59 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 1954.31 on 1532 degrees of freedom Residual deviance: 940.36 on 1531 degrees of freedom (790 observations deleted due to missingness) AIC: 944.36 Number of Fisher Scoring iterations: 5

What is the predicted probability of voting for McCain at the minimum value of partyid7.n? What about at the maximum value.

minimum: 0.02222786

Maximum:0.9525673

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