PREDICTIVE MODELLING EXAMINATION QUESTIONS AND CORRECT ANSWER WITH EXPLANATION GRADED A+ STUDY GUIDE

PREDICTIVE MODELLING EXAMINATION QUESTIONS
AND CORRECT ANSWER WITH EXPLANATION GRADED
A+ STUDY GUIDE SOUTHERN NEW HAMPSHIRE
UNIVERSITY
1. Predictive modelling is used to:
A. Predict future outcomes using data
B. Draw pictures only
C. Write essays
D. Store files only
Answer: A
Rationale: It forecasts future events using data patterns.

2. A predictive model is:
A. Mathematical representation of relationships
B. Random guess
C. Drawing tool
D. Text document
Answer: A
Rationale: Models relationships between variables.

3. Dependent variable is:
A. Output to be predicted
B. Input variable
C. Constant value
D. Error term
Answer: A
Rationale: Target variable.

4. Independent variable is:
A. Predictor variable
B. Output variable
C. Error only
D. Constant
Answer: A
Rationale: Input feature.

,5. Feature in modelling refers to:
A. Input variable
B. Output variable
C. Error
D. Graph only
Answer: A
Rationale: Predictive input.

6. Target variable is:
A. What we predict
B. Input data
C. Noise
D. Constant
Answer: A
Rationale: Outcome variable.

7. Training data is used to:
A. Build the model
B. Test model only
C. Ignore data
D. Draw graphs
Answer: A
Rationale: Model learning.

8. Testing data is used to:
A. Evaluate model performance
B. Build model
C. Store data
D. Ignore errors
Answer: A
Rationale: Model evaluation.

9. Validation data is used to:
A. Tune model parameters
B. Ignore model
C. Build graphs
D. Store results
Answer: A
Rationale: Model optimization.

, 10. Overfitting occurs when:
A. Model learns noise too well
B. Model is too simple
C. No data used
D. Random guessing
Answer: A
Rationale: Poor generalization.

11. Underfitting occurs when:
A. Model is too simple
B. Model is too complex
C. Perfect fit
D. Random fit
Answer: A
Rationale: Insufficient learning.

12. Bias in modelling refers to:
A. Systematic error
B. Random error
C. Accuracy
D. Precision
Answer: A
Rationale: Consistent deviation.

13. Variance refers to:
A. Model sensitivity to data
B. Mean value
C. Constant value
D. Fixed output
Answer: A
Rationale: Fluctuation measure.

14. Bias-variance tradeoff is about:
A. Balancing error types
B. Increasing data only
C. Reducing graphs
D. Ignoring data
Answer: A
Rationale: Model optimization.