Linear Regression Residuals

Use Desmos to generate the linear regression model for this data set. What is the residual for the point (31, 560)? (round to nearest hundredth)

• 2.48

• -15.79

• -7.52

• 12.87

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

The residual plots from five different least squares regression lines are shown below. Which of the plots shows the strongest evidence that its regression line is an appropriate model for the data and is consistent with the assumptions required for inference for regression?

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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

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 line of regression is y = 3.45x - 6.7 and the actual point is (5,12), what is the residual for that point?

• 1.45

• -1.45

• 34.7

• -34.7

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

• YES

• NO

I predicted someone would score a 78% on their test, but they actually scored an 81%. What's the residual?

• 81 - 78 = 3

• 78 - 81 = -3

• What's residual?