Question 1

Given the regression equation $$	ext{Books} = -0.688 + 1.5498 	imes 	ext{Classes}$$, what is the correct interpretation of the slope in this context?

Accepted Answer

For each additional class a student takes, the number of books they own increases by 1.5498 on average.

Question 2

In the regression equation $$	ext{Books} = -0.688 + 1.5498 	imes 	ext{Classes}$$, does the intercept have a meaningful interpretation?

Accepted Answer

No, because it predicts a negative number of books when the number of classes is zero, which is not possible.

Question 3

Using the regression equation $$	ext{Books} = -0.688 + 1.5498 	imes 	ext{Classes}$$, predict the number of books for a student taking 5 classes.

Accepted Answer

$$7.061$$

Question 4

Which of the following is NOT a condition that must be checked before fitting a linear regression model?

Accepted Answer

The variables must be qualitative.

Question 5

A residual is defined as:

Accepted Answer

The difference between the observed y-value and the predicted y-value.

Question 6

If the residual plot shows a curved pattern, what does this indicate?

Accepted Answer

The relationship between x and y is not linear.

Question 7

What does $$R^2$$ represent in a regression analysis?

Accepted Answer

The proportion of the variance in y explained by x.

Question 8

A regression analysis between central pressure and maximum wind speed in hurricanes gives $$R^2 = 0.803$. What does this mean?

Accepted Answer

80.3% of the variability in maximum wind speed is explained by central pressure.

Question 9

Which of the following statements about outliers in regression is TRUE?

Accepted Answer

An influential outlier can significantly change the slope and $$R^2 if $$removed.

Question 10

Which of the following is an example of a lurking variable?

Accepted Answer

Blood volume affecting the relationship between number of beers and blood alcohol content.

Question 11

Why should you avoid extrapolating predictions far outside the range of your data in regression analysis?

Accepted Answer

The relationship observed within the data range may not hold outside that range.

Question 12

Which of the following best describes the meaning of the standard deviation of the residuals ($$s_e) in $$regression?

Accepted Answer

It measures the typical prediction error when using the regression line.

Question 13

A regression analysis finds $$r = 0. $$What does this mean?

Accepted Answer

There is no linear relationship between x and y.

Question 14

Which of the following is a correct interpretation of the regression slope in the context of sugar and calories in cereal, given $$\hat{y} = 89.6 + 2.49x$$?

Accepted Answer

Cereals that have one gram more sugar tend to have 2.49 more calories on average.

Question 15

Which of the following is NOT a reason to be cautious about claiming causation from a regression analysis?

Accepted Answer

A high $$R^2$$ always proves causation.

Question 16

Which of the following residual plots indicates that a linear model is appropriate?

Accepted Answer

A plot where residuals are randomly scattered around zero with no pattern.

Question 17

If removing a data point from a regression analysis changes the slope and $$R^2$$ dramatically, what is this point called?

Accepted Answer

An influential outlier.

Question 18

Which of the following is true about the correlation coefficient $$r$$?

Accepted Answer

It is not resistant to outliers.

Question 19

A regression model for used cars is $$	ext{Price} = 17673.965 - 844.46389 	imes 	ext{Age}. $$What does the slope mean?

Accepted Answer

For each additional year of age, the price decreases by about $844.46.

Regression, Correlation, and Residual Analysis in Introductory Statistics

Study Guide - Practice Questions

Study Guide - Flashcards