Linear Residuals

• 50 miles

• -50 miles

• 8 miles

• -25 miles

When using midterm exam scores to predict a student's final grade in the class, the student would prefer to have

• positive residual, because that means the student's final grade is higher than we would predict with the model

• positive residual, because that means the student's final grade is lower than we would predict with the model

• residual equal to zero, because that means the student’s final grade is exactly what we would predict with the model

• negative residual, because that means the student’s final grade is higher than we would predict with the model

• This residual plot represents a linear fit.
• This residual plot represents a nonlinear fit.
• This residual plot represents no fit.

Residuals are . . . 

• possible models not explored by the researcher

• variation in the response variable that is explained by the model

• the difference between the observed response and the values predicted by the model

• data collected from individuals that is not consistent with the rest of the group

Use Desmos to generate a linear regression model. What is the residual for the point (5, 96)? Round to the nearest hundredth.

• 2.34

• -0.31

• -0.53

• 3.67

Use the dropdowns to complete the statements about the graph:

The strength of the linear relationship is ​ (a)   (strong/weak) because the residual values are relatively ​ (b)   (small/large) . The residuals on the graph ​ (c)   (show/do not show) a pattern.

• weak

• strong

• large

• small

• show

• do not show

Question 9

• 1

• 2

• 3

• 4

Use the dropdowns to complete the statements about the graph: The strength of the linear relationship is ​ (a)   (strong/weak) because the residual values are relatively ​ (b)   (small/large) . The residuals on the graph ​ (c)   (show/do not show) a pattern.

• weak

• strong

• large

• small

• show

• do not show

• 
• 
• 
• 

• A

• B

• C

• D