SAS Data Scientist Predictive Modeling Quiz

1. The Area Under the Curve (AUC) metric evaluates which aspect of a classifier?

Prediction speed

Discrimination ability across thresholds

Feature importance

Model complexity

2. Which metric is calculated as TP / (TP + FP) in classification?

Recall

Precision

Accuracy

Specificity

3. What is the purpose of stratified sampling in model development?

Reduce data size

Maintain class distribution in train/test splits

Remove outliers

Improve variable scaling

4. In SAS, which PROC statement is used for variable selection in regression?

PROC REG with SELECTION

PROC SELECT

PROC STEPWISE

PROC CHOOSE

5. Which approach combines multiple weak learners into a stronger predictor?

Regularization

Ensemble methods

Feature selection

Data imputation

6. The residuals in a regression model should exhibit which property?

Normal distribution

Positive skewness

High correlation

Exponential growth

7. What does sensitivity (recall) measure in a classification model?

Proportion of positives correctly identified

Proportion of negatives correctly identified

Overall prediction accuracy

Prediction confidence

8. Which regularization technique helps prevent overfitting by adding a penalty term?

Bagging

Ridge regression

Boosting

Stratification

9. In SAS, which statement is used to specify the target variable in PROC LOGISTIC?

MODEL

CLASS

VAR

TARGET

10. What is the primary goal of principal component analysis (PCA)?

Remove missing values

Reduce dimensionality while retaining variance

Balance class distributions

Detect outliers

11. Which SAS procedure is primarily used for logistic regression in predictive modeling?

PROC REG

PROC LOGISTIC

PROC GENMOD

PROC GLMSELECT

12. Which SAS procedure implements random forest models?

PROC FOREST

PROC HPFOREST

PROC ENSEMBLE

PROC RF

13. What is multicollinearity in predictive modeling?

High correlation among predictor variables

Unequal variance in residuals

Non-linear relationships

Missing data patterns

14. Which performance metric measures the proportion of correctly predicted cases?

Precision

Recall

Accuracy

AUC

15. In model validation, what does the holdout method involve?

Using all data for training

Partitioning data into train and test sets

Removing outliers before modeling

Standardizing all variables

16. Which SAS procedure is used for decision tree modeling?

PROC HPFOREST

PROC TREE

PROC SPLIT

PROC CARTTREE

17. What is the primary purpose of feature scaling in predictive modeling?

Reduce dimensionality

Normalize variables to comparable ranges

Eliminate outliers

Improve interpretability

18. Which metric is most appropriate for imbalanced classification problems?

Accuracy

F1-score

Sensitivity

Specificity

19. In a confusion matrix, what does true positive (TP) represent?

Correctly predicted positive cases

Incorrectly predicted positive cases

Correctly predicted negative cases

Incorrectly predicted negative cases

20. What does cross-validation help prevent in predictive models?

Underfitting

Overfitting

Multicollinearity

Heteroscedasticity

SAS Data Scientist Predictive Modeling Quiz

1. The Area Under the Curve (AUC) metric evaluates which aspect of a classifier?

2.

What first name or nickname would you like us to use?

2. Which metric is calculated as TP / (TP + FP) in classification?

3. What is the purpose of stratified sampling in model development?

4. In SAS, which PROC statement is used for variable selection in regression?

5. Which approach combines multiple weak learners into a stronger predictor?

6. The residuals in a regression model should exhibit which property?

7. What does sensitivity (recall) measure in a classification model?

8. Which regularization technique helps prevent overfitting by adding a penalty term?

9. In SAS, which statement is used to specify the target variable in PROC LOGISTIC?

10. What is the primary goal of principal component analysis (PCA)?

11. Which SAS procedure is primarily used for logistic regression in predictive modeling?

12. Which SAS procedure implements random forest models?

13. What is multicollinearity in predictive modeling?

14. Which performance metric measures the proportion of correctly predicted cases?

15. In model validation, what does the holdout method involve?

16. Which SAS procedure is used for decision tree modeling?

17. What is the primary purpose of feature scaling in predictive modeling?

18. Which metric is most appropriate for imbalanced classification problems?

19. In a confusion matrix, what does true positive (TP) represent?

20. What does cross-validation help prevent in predictive models?