11.4.3 WP Consider the following computer output. The regression equation is Y = 12.9 + 2.34 x Predictor Constant Coef 12.857 Regression Residual error Total 2.3445 Analysis of Variance Source 1.032 X 0.1150 ? S = 1.48111 R-sq = 98.1% R-sq (adj) = 97.9% SE Coef DF 1 8 9 T ? SS 912.43 17.55 929.98 P ? ? MS F P 912.43 ? ? ? a. Fill in the missing information. You may use bounds for the P-values. b. Can you conclude that the model defines a useful linear relationship? c. What is your estimate of o²?

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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11.4.3 WP Consider the following computer output.
The regression equation is
Y = 12.9 + 2.34 x
Predictor
Constant
Coef
12.857
X
S = 1.48111 R-sq = 98.1%
Regression
Residual error
Total
2.3445
Analysis of Variance
Source
DF
1
8
9
SE Coef
T
?
?
R-sq(adj) = 97.9%
1.032
0.1150
P
?
SS
912.43
17.55
929.98
?
MS F P
912.43 ? ?
?
a. Fill in the missing information. You may use bounds for
the P-values.
b. Can you conclude that the model defines a useful linear
relationship?
c. What is your estimate of o²?
Transcribed Image Text:11.4.3 WP Consider the following computer output. The regression equation is Y = 12.9 + 2.34 x Predictor Constant Coef 12.857 X S = 1.48111 R-sq = 98.1% Regression Residual error Total 2.3445 Analysis of Variance Source DF 1 8 9 SE Coef T ? ? R-sq(adj) = 97.9% 1.032 0.1150 P ? SS 912.43 17.55 929.98 ? MS F P 912.43 ? ? ? a. Fill in the missing information. You may use bounds for the P-values. b. Can you conclude that the model defines a useful linear relationship? c. What is your estimate of o²?
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