For the logistic regression model fitted to the training set, what is the coefficient for the KIDSDRIV variable? (Round to two decimal places)

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Question 4 (1 point)

Listen

For the logistic regression model fitted to the training set, what is the odds ratio for the URBANICITY variable? (Round to two decimal places).

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Question 5 (1 point)

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How would you interpret the odds ratio for the URBANICITY variable?

Question 5 options:

	If a customer lives in an urban area, the odds of submitting an auto insurance claim increase by 10.73 times on average, holding all other variables constant.
	If a customer lives in an urban area, the odds of submitting an auto insurance claim decrease by 10.73 times on average, holding all other variables constant.
	If a customer lives in a rural area, the odds of submitting an auto insurance claim decrease by 10.73 times on average, holding all other variables constant.
	If a customer lives in a rural area, the odds of submitting an auto insurance claim increase by 10.73 times on average, holding all other variables constant.

Question 6 (1 point)

Listen

According to the confusion matrix, how many insurance claims (positives) did the model predict correctly?

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Question 7 (1 point)

Listen

What is the accuracy rate? (Report as a percentage and round to two decimal places)

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Question 8 (1 point)

Listen

What is the sensitivity? (Report as a percentage and round to two decimal places).

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Question 9 (1 point)

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How would you interpret the sensitivity?

Question 9 options:

	It is the accuracy rate of predicting that customers will make insurance claims.
	It is the accuracy rate of predicting that customers will not make insurance claims.
	It is the inverse of the overall error rate for the logistic regression model.
	It is the overall error rate for the logistic regression model.

Question 10 (1 point)

Listen

What is the AUC for the ROC Curve you just generated? (Round to two decimal places)

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Question 11 (1 point)

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In this new training subset generated from oversampling, how many observations are in the class that has made a recent auto claim ("Yes")?

Question 11 options:

Question 12 (1 point)

Listen

What is the accuracy rate based on the new confusion matrix? (Report as a percentage and round to two decimal places)

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Question 13 (1 point)

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What is the sensitivity? (Report as a percentage and round to two decimal places).

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Question 14 (1 point)

Listen

What is the AUC for the new ROC Curve you just generated? (Round to two decimal places)

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Question 15 (1 point)

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What do you notice about this AUC value as compared to the AUC value generated from the previous logistic regression model?

Question 15 options:

	This AUC value is significantly larger than the first AUC value.
	This AUC value is significantly smaller than the first AUC value.
	There is not a large difference between the two AUC values.

Question 16 (1 point)

Listen

Based on this new confusion matrix, how many insurance claims (positives) did the model predict correctly using the test set?

Question 16 options:

Question 17 (1 point)

Listen

What is the accuracy rate? (Report as a percentage and round to two decimal places).

Question 17 options:

Question 18 (1 point)

Listen

What is the sensitivity? (Report as a percentage and round to two decimal places).

Question 18 options:

Question 19 (1 point)

Listen

What is the AUC for the new ROC Curve you just generated? (Round to two decimal places)

Question 19 options:

Question 20 (1 point)

Listen

What is the predicted probability of making an insurance claim for new customer #1? (Round to two decimal places).

Question 20 options: