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F. Use variables 2 to 8 to determine which of the predictors inuence the probability that an application is accepted. Use the summary function to

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F. Use variables 2 to 8 to determine which of the predictors inuence the probability that an application is accepted. Use the summary function to print the results. (10 points) inine Quiz will be based on the following and related concepts: a. Do any of the predictors appear to be statistically significant? If so, which ones? Explain how each of the significant predictors inuences the response variable. G. To predict whether the application will be accepted or not: convert the predicted probabilities into class labels yes with the following condition: probs }.5=\"yes". Compute the confusion matrix and overall fraction of correct predictions. (30 points) inine Quiz will be based on the following and related questions: a. Explain what the confusion matrix is telling you about the types of mistakes made by logistic regression (false positive, false negative, overall correct predictions). H. Now fit the logistic regression model using a training data for observations 1 to 1000. Compute the confusion matrix and the overall fraction of correct predictions for the test data [that is, the data for observations 1001 to end of data.) (30 points) Online Quiz will be based on the following and related questions: a. Explain what the confusion matrix is telling you about the types of mistakes made by logistic regression (false positive: false negative, overall correct predictions). Useful hints: l\" Run the g]rn() logistic regression on the training data. 2. Use test data in the predict() function to predict the card acceptance probability on the test observations on the basis of the predicted model. 3. To predict whether a card will be accepted [yesfno), convert the predicted probabilities into class labels \"yes'r or "no" on the test data

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