The accompanying values are a set of data for y, the amount of money (in thousands of dollars) contributed to the alumni association at a certain university from a certain graduate class, and x, the number of years following graduation for that class. Complete parts (a) through (c) below. Click the icon to view the contribution data. (a) Fit a regression model of the type μy|x = ẞo +ẞ1×1 ŷ= -587 + (428) ×₁ (Round to the nearest integer as needed.) (b) Fit a quadratic model of the type μyx = 0 + ẞ₁×₁ + B₁₁ײ₁. y = 1980 + ( - 192) + (352) xỉ (Round the x-coefficient to one decimal place as needed. Round all other constants and coefficients to the nearest integer as needed.) (c) Determine which of the models in (a) or (b) is preferable. Use s², R², and the PRESS residuals to support the decision. Compute s² for each model. Model s² Hylx =Bo+B₁x1 1104727 (Round to the nearest integer as needed.) Compute R² for each model. Model R² Hylx Bo+B1x1 (Round to three decimal places as needed.) 430563 Contribution Data y x y x 812.48 1 2752.00 11 824.50 2 4391.50 12 1210.50 3 5580.50 13 1348.00 4 5549.00 14 1301.00 8 6089.00 15 2566.50 9 5763.00 2529.50 10 8901.00 197 16

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I need help to find R^2 and Press final answers. Everything needed is attached also the contribution data.

The accompanying values are a set of data for y, the amount of money (in thousands of dollars) contributed to the alumni association at a certain university from a certain graduate class, and x, the number of years following graduation for that class. Complete parts (a) through (c)
below.
Click the icon to view the contribution data.
(a) Fit a regression model of the type μy|x = ẞo +ẞ1×1
ŷ= -587 + (428) ×₁
(Round to the nearest integer as needed.)
(b) Fit a quadratic model of the type μyx = 0 + ẞ₁×₁ + B₁₁ײ₁.
y = 1980 + ( - 192) + (352) xỉ
(Round the x-coefficient to one decimal place as needed. Round all other constants and coefficients to the nearest integer as needed.)
(c) Determine which of the models in (a) or (b) is preferable. Use s², R², and the PRESS residuals to support the decision.
Compute s² for each model.
Model
s²
Hylx =Bo+B₁x1
1104727
(Round to the nearest integer as needed.)
Compute R² for each model.
Model
R²
Hylx Bo+B1x1
(Round to three decimal places as needed.)
430563
Transcribed Image Text:The accompanying values are a set of data for y, the amount of money (in thousands of dollars) contributed to the alumni association at a certain university from a certain graduate class, and x, the number of years following graduation for that class. Complete parts (a) through (c) below. Click the icon to view the contribution data. (a) Fit a regression model of the type μy|x = ẞo +ẞ1×1 ŷ= -587 + (428) ×₁ (Round to the nearest integer as needed.) (b) Fit a quadratic model of the type μyx = 0 + ẞ₁×₁ + B₁₁ײ₁. y = 1980 + ( - 192) + (352) xỉ (Round the x-coefficient to one decimal place as needed. Round all other constants and coefficients to the nearest integer as needed.) (c) Determine which of the models in (a) or (b) is preferable. Use s², R², and the PRESS residuals to support the decision. Compute s² for each model. Model s² Hylx =Bo+B₁x1 1104727 (Round to the nearest integer as needed.) Compute R² for each model. Model R² Hylx Bo+B1x1 (Round to three decimal places as needed.) 430563
Contribution Data
y
x
y
x
812.48
1
2752.00
11
824.50
2
4391.50
12
1210.50
3
5580.50 13
1348.00
4
5549.00 14
1301.00
8
6089.00
15
2566.50
9
5763.00
2529.50
10
8901.00
197
16
Transcribed Image Text:Contribution Data y x y x 812.48 1 2752.00 11 824.50 2 4391.50 12 1210.50 3 5580.50 13 1348.00 4 5549.00 14 1301.00 8 6089.00 15 2566.50 9 5763.00 2529.50 10 8901.00 197 16
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