Data Science Analysis 5

Question 1

In a simple linear regression, the R-squared value represents:

Accepted Answer

The proportion of variance in the target explained by the model

Answer

R-squared measures how much of the target's variability the model accounts for.

Question 2

A residual plot showing a clear curved pattern suggests:

Accepted Answer

The linear model may be misspecified

Answer

Structure in residuals indicates the linear form fails to capture the true relationship.

Question 3

Which metric is most appropriate for evaluating a regression model's prediction error?

Accepted Answer

Root mean squared error (RMSE)

Answer

RMSE measures average prediction error magnitude for continuous targets.

Question 4

On an imbalanced classification dataset, why can accuracy be misleading?

Accepted Answer

A model predicting the majority class can score high while ignoring the minority

Answer

With skewed classes, always predicting the common class yields high accuracy but poor minority detection.

Question 5

What does precision measure in a classification model?

Accepted Answer

The fraction of predicted positives that are actually positive

Answer

Precision is true positives divided by all predicted positives.

Data Science Practice Test