Multiple Chоice Questiоns 32-33 The fоllowing tаble shows the R output of а logistic regression model, where the vаriables Sepal.Length, Sepal.Width, Petal.Length, and Petal.Width are predictors and the variable virginica is the response. Using the following R output from a fitted logistic regression model, answer Questions 32 and 33. Call:glm(formula = virginica ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, family = binomial, data = iris)Deviance Residuals: Min 1Q Median 3Q Max -2.01105 -0.00065 0.00000 0.00048 1.78065 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -42.638 25.708 -1.659 0.0972 .Sepal.Length -2.465 2.394 -1.030 0.3032 Sepal.Width -6.681 4.480 -1.491 0.1359 Petal.Length 9.429 4.737 1.990 0.0465 *Petal.Width 18.286 9.743 1.877 0.0605 .---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1(Dispersion parameter for binomial family taken to be 1) Null deviance: 190.954 on 149 degrees of freedomResidual deviance: 11.899 on 145 degrees of freedomAIC: 21.899
Multiple Chоice Questiоns 32-33 The fоllowing tаble shows the R output of а logistic regression model, where the vаriables Sepal.Length, Sepal.Width, Petal.Length, and Petal.Width are predictors and the variable virginica is the response. Using the following R output from a fitted logistic regression model, answer Questions 32 and 33. Call:glm(formula = virginica ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, family = binomial, data = iris)Deviance Residuals: Min 1Q Median 3Q Max -2.01105 -0.00065 0.00000 0.00048 1.78065 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -42.638 25.708 -1.659 0.0972 .Sepal.Length -2.465 2.394 -1.030 0.3032 Sepal.Width -6.681 4.480 -1.491 0.1359 Petal.Length 9.429 4.737 1.990 0.0465 *Petal.Width 18.286 9.743 1.877 0.0605 .---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1(Dispersion parameter for binomial family taken to be 1) Null deviance: 190.954 on 149 degrees of freedomResidual deviance: 11.899 on 145 degrees of freedomAIC: 21.899
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