Residuals Versus EDUC Residuals Versus AGE (rosponse is INCOME) (responee is INCOME) 10- 10 -10- -10 20 20 10 15 20 40 50 EDUC (a) AGE (b) Residuals Versus the Fitted Values Normal Probability Plot of the Residuals (response is INCOME) (reeponse is INCOME) 25 20- 10 1.5- 1.0 0.5- 0.0 -0.5- 1.0- -10- -15- -2.0- -25 -20 10 10 -10 20 40 50 60 70 Residual Fitted Value (4) (c) jenpisoy jenpreou Normal Score Residual

Question

Annual Income. Refer to Problem 18. OutputsA.22(a), (b), and (c) on page A-62 display, respectively, plots of residuals against education, residuals against age, and residuals against predicted income; Output A.22(d) shows a normal probability plot of the residuals. Do these graphs suggest any violations of the assumptions for multiple linear regression inferences for the variables under consideration? 

Residuals Versus EDUC
Residuals Versus AGE
(rosponse is INCOME)
(responee is INCOME)
10-
10
-10-
-10
20
20
10
15
20
40
50
EDUC
(a)
AGE
(b)
Residuals Versus the Fitted Values
Normal Probability Plot of the Residuals
(response is INCOME)
(reeponse is INCOME)
25
20-
10
1.5-
1.0
0.5-
0.0
-0.5-
1.0-
-10-
-15-
-2.0-
-25
-20
10
10
-10
20
40
50
60
70
Residual
Fitted Value
(4)
(c)
jenpisoy
jenpreou
Normal Score
Residual
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Transcribed Image Text

Residuals Versus EDUC Residuals Versus AGE (rosponse is INCOME) (responee is INCOME) 10- 10 -10- -10 20 20 10 15 20 40 50 EDUC (a) AGE (b) Residuals Versus the Fitted Values Normal Probability Plot of the Residuals (response is INCOME) (reeponse is INCOME) 25 20- 10 1.5- 1.0 0.5- 0.0 -0.5- 1.0- -10- -15- -2.0- -25 -20 10 10 -10 20 40 50 60 70 Residual Fitted Value (4) (c) jenpisoy jenpreou Normal Score Residual