Question

In: Statistics and Probability

We give JMP output of regression analysis. Above output we give the regression model and the...

We give JMP output of regression analysis. Above output we give the regression model and the number of observations, n, used to perform the regression analysis under consideration. Using the model, sample size n, and output:


Model: y = β0+ β1x1+ β2x2+ β3x3+ ε       Sample size: n = 30

Summary of Fit
RSquare 0.956255
RSquare Adj 0.951207
Root Mean Square Error 0.240340
Mean of Response 8.382667
Observations (or Sum Wgts) 30
Analysis of Variance
Source df Sum of
Squares
Mean
Square
F Ratio
Model 3 32.829545 10.94320 189.4492
Error 26 1.501842 0.05780 Prob > F
C. Total 29

34.331387


(1) Report the total variation, unexplained variation, and explained variation as shown on the output. (Round your answers to 4 decimal places.)

Total variation
unexplained variation
explained variation

(2) Report R2 and R¯¯¯2 as shown on the output. (Round your answers to 4 decimal places.)
R^2
-
R2

(3) Report SSE, s2, and s as shown on the output. (Round your answers to 4 decimal places.)
SSE
S^2

(4) Calculate the F(model) statistic by using the explained variation, the unexplained variation, and other relevant quantities. (Round your answer to 2 decimal places.)
F(model)

(6) Find the p−value related to F(model) on the output. Using the p−value, test the significance of the linear regression model by setting α = .10, .05, .01, and .001. What do you conclude?

p-value =.0000. Since this p-value is less than α =.001, we have       evidence
that H0: β1 = β2 = β3 =0 is false. That is, we have       evidence
that at least one of x1, x2 ,and x3is significantly related to y.

<.0001*

Solutions

Expert Solution

(1) Report the total variation, unexplained variation, and explained variation as shown on the output. (Round your answers to 4 decimal places.)

Total variation:100%
unexplained variation:95.63%
explained variation:100-95.63=4.37%

2) Report R2 and R¯¯¯2 as shown on the output. (Round your answers to 4 decimal places.)
R^2=0.9563
-
R2=0.9512

3) Report SSE, s2, and s as shown on the output. (Round your answers to 4 decimal places.)
SSE=1.5018
S^2=MSE=0.0578

s=sqrt(MSE)=0.2404

(4) Calculate the F(model) statistic by using the explained variation, the unexplained variation, and other relevant quantities. (Round your answer to 2 decimal places.)
F(model)=MS Square Error/MS Model=10.94320.05780=189.45

6) Find the p−value related to F(model) on the output. Using the p−value, test the significance of the linear regression model by setting α = .10, .05, .01, and .001.

p-value =.0000. Since this p-value is less than α =0.1, we have       evidence
that H0: β1 = β2 = β3 =0 is false. That is, we have       evidence
that at least one of x1, x2 ,and x3is significantly related to y.

p-value =.0000. Since this p-value is less than α =0.05, we have       evidence
that H0: β1 = β2 = β3 =0 is false. That is, we have       evidence
that at least one of x1, x2 ,and x3is significantly related to y.

p-value =.0000. Since this p-value is less than α =0.01, we have       evidence
that H0: β1 = β2 = β3 =0 is false. That is, we have       evidence
that at least one of x1, x2 ,and x3is significantly related to y.

p-value =.0000. Since this p-value is less than α =0.001, we have       evidence
that H0: β1 = β2 = β3 =0 is false. That is, we have       evidence
that at least one of x1, x2 ,and x3is significantly related to y.


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