AP Statistics Chapter 3

What does the correlation coefficient (r) measure?

• The direction and strength of the linear relationship between two quantitative variables

• The average size of the residuals in a regression model

• The percentage of variation in the response variable accounted for by the regression line

• The difference between the observed and predicted values in a regression model

What does the coefficient of determination (r^2) represent?

• The proportion of variation in the response variable explained by the regression line

• The average size of the residuals in a regression model

• The slope of the regression line

• The y-intercept of the regression line

Identify the term being interpreted below: "About 45% of the variability of height (y) can be accounted for by the LSRL for weight (x)."

• slope

• y-intercept

• standard deviation of the residuals (S)

• coefficient of determination (r^2)

Identify the term being interpreted below:"With each additional pound of weight (x) the predicted (y) increases by 5"

• slope

• y-intercept

• standard deviation of the residuals (S)

• coefficient of determination (r^2)

• A

• B

• C

• D

• E

Is this a probability distribution?

• No, the sum of p(x) does not equal 1.

• Yes, all p(x) are between 0 and 1.

• No, all p(x) are not between 0 and 1.

• Yes, the sum p(x) is 1.

Is this a probability distribution?

• No

• Yes

LSRL stands for

• Least Sum Regression Line

• Least Squares Regression Line

• Lower Standard Regression Line

• Line Scatterplot Regression Line

Which of the following statements about correlation is true?

• Correlation does not imply causation

• Correlation is resistant to outliers

• Correlation can only describe linear relationships

• Correlation is influenced by the units of measurement

What is an outlier in the context of regression?

• An observation that lies outside the overall pattern of the other observations

• A point that is extreme in the y direction of a scatterplot

• A point that is extreme in the x direction of a scatterplot

• An observation that has a large residual