The following estimated regression equation based on 10 observations was presented. ŷ = 26.1570+ 0.5205x₁ +0.495x2 502 Here, SST = 6,721.125, SSR = 6,212.375, Sb₁ = 0.0816, and (a) Compute MSR and MSE. = 0.0568. (b) Compute F and perform the appropriate F test. Use a = 0.05. (c) Perform a t test for the significance of ₁. Use α = 0.05.
The following estimated regression equation based on 10 observations was presented. ŷ = 26.1570+ 0.5205x₁ +0.495x2 502 Here, SST = 6,721.125, SSR = 6,212.375, Sb₁ = 0.0816, and (a) Compute MSR and MSE. = 0.0568. (b) Compute F and perform the appropriate F test. Use a = 0.05. (c) Perform a t test for the significance of ₁. Use α = 0.05.
A First Course in Probability (10th Edition)
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Transcribed Image Text:502
Here, SST = 6,721.125, SSR = 6,212.375, sh = 0.0816, and s
The following estimated regression equation based on 10 observations was presented.
y = 26.1570 +0.5205x₁ + 0.495x2
(a) Compute MSR and MSE.
(b) Compute F and perform the appropriate F test. Use α = 0.05.
(c) Perform a t test for the significance of ₁. Use α = 0.05.
(d) Perform a t test for the significance of $₂. Use a = 0.05.
Step 1
(a) Compute MSR and MSE.
The MSR, mean square due to regression is calculated as follows where SSR is the sum of squares due to regression
and p is the number of independent variables in the estimated regression equation.
MSR =
MSR =
The estimated regression equation was given to be y = 26.1570+ 0.5205x₁ + 0.495x₂. This equation has two
independent variables, so p = 0.05
X . The value of SSR was given to be SSR = 6,212.375. Use these to find
the value of MSR, rounding the result to three decimal places.
SSR
Р
2
= 0.0568.
SSR
P
6,212.375
3106.1875
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