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Question 1

Your dependent variable Y is a count, ranging from 0 to infinity. Because Y is approximately log-normally distributed, you decide to log-transform the data prior to performing a linear regression. What should you do before log-transforming Y?

Options :

A : Add 1 to all of the Y values.

B : Divide all the Y values by the standard deviation of Y.

C : Explore the data for outliers.

D : Subtract the mean of Y from all the Y values.

Answer: A

Question 2

Which of the following is the definition of accuracy?

Options :

A : (True Positives + False Positives) / Total Predictions

B : (True Positives + True Negatives) / Total Predictions

C : True Positives / (True Positives + False Negatives)

D : True Positives / (True Positives + False Positives)

Answer: B

Question 3

Which of the following options is a correct approach for scheduling model retraining in a weather prediction application?

Options :

A : As new resources become available

B : Once a month

C : When the input format changes

D : When the input volume changes

Answer: C

Question 4

A classifier has been implemented to predict whether or not someone has a specific type of disease. Considering that only 1% of the population in the dataset has this disease, which measures will work the BEST to evaluate this model?

Options :

A : Mean squared error

B : Precision and accuracy

C : Precision and recall

D : Recall and explained variance

Answer: C

Question 5

Which of the following is NOT a valid cross-validation method?

Options :

A : Bootstrapping

B : K-fold

C : Leave-one-out

D : Stratification

Answer: D