Residuals and Correlation Coefficient

A negative residual means...

• that the predicted value is too big

• that the predicted value is too small

• that the x value is too big

• that the x value is too small

Tags

CCSS.HSF-LE.A.1B

• Positive, strong
• Positive, weak
• Negative, strong
• Negative weak

Tags

CCSS.HSF-LE.A.1B

Shown is a residual plot. How many negative residuals are there?

• 5

• 1

• 3

• 9

Shown is a residual plot. How many zero residuals are there?

• 5

• 1

• 3

• 0

A positive residual means...

• that the predicted value is too big

• that the predicted value is too small

• that the x value is too big

• that the x value is too small

Tags

CCSS.HSF.LE.B.5

Shown is a residual plot. Would a linear regression model of the data be most appropriate?

• YES

• NO

Shown is a residual plot. How many positive residuals are there?

• 5

• 1

• 3

• 9

If the point with the red x is removed from the scatterplot, what will happen to the slope of the LSRL and the correlation coefficient?

• slope increases, r increases

• slope decreases, r increases

• slope increases, r decreases

• slope decreases, r decreases

• slope is unchanged, r increases

Estimate the correlation coefficient.

• r = -0.8

• r = -0.5

• r = 0.5

• r = 0.8

Estimate the correlation coefficient for this scatterplot.

• r = 1.2

• r = 0.89

• r = 0

• r = -0.89