A social scientist would like to predict perceived conflict resolution skill level from a set of five predictor variables for a sample of 36 teachers. A multiple linear regression analysis was conducted. Complete the following ANOVA summary table for the test of significance of the overall regression model. Except for the P-value, report all answers accurate to 3 decimal places; report the P-value accurate to 4 decimal places. Use a significance level of a = 0.02. sS df Source MS P.value Regression 25 Residual 398 TOTAL What is your decision for the hypothesis test? O Reject the null hypothesis, Ho: B1 = B2 = . = ßs = 0 OFail to reject Ho What is your final conclusion? O The evidence supports the claim that one or more of the regression coefficients is non-zero O The evidence supports the claim that all of the regression coefficients are zero O There is insufficient evidence to support the claim that at least one of the regression coefficients is non-zero OThere is insufficient evidence to support the claim that all of the regression coefficients are equal to zero 00

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 4GP
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A social scientist would like to predict perceived conflict resolution skill level from a set of five
predictor variables for a sample of 36 teachers. A multiple linear regression analysis was
conducted. Complete the following ANOVA summary table for the test of significance of the
overall regression model. Except for the P-value, report all answers accurate to 3 decimal places;
report the P-value accurate to 4 decimal places. Use a significance level of a = 0.02.
Source
df
MS
F
P-value
Regression
25
Residual
398
TOTAL
What is your decision for the hypothesis test?
O Reject the null hypothesis, Ho: B1 = B2 = ... = Bs = 0
O Fail to reject Ho
What is your final conclusion?
OThe evidence supports the claim that one or more of the regression coefficients is non-zero
OThe evidence supports the claim that all of the regression coefficients are zero
OThere is insufficient evidence to support the claim that at least one of the regression
coefficients is non-zero
OThere is insufficient evidence to support the claim that all of the regression coefficients are
equal to zero
00
Transcribed Image Text:A social scientist would like to predict perceived conflict resolution skill level from a set of five predictor variables for a sample of 36 teachers. A multiple linear regression analysis was conducted. Complete the following ANOVA summary table for the test of significance of the overall regression model. Except for the P-value, report all answers accurate to 3 decimal places; report the P-value accurate to 4 decimal places. Use a significance level of a = 0.02. Source df MS F P-value Regression 25 Residual 398 TOTAL What is your decision for the hypothesis test? O Reject the null hypothesis, Ho: B1 = B2 = ... = Bs = 0 O Fail to reject Ho What is your final conclusion? OThe evidence supports the claim that one or more of the regression coefficients is non-zero OThe evidence supports the claim that all of the regression coefficients are zero OThere is insufficient evidence to support the claim that at least one of the regression coefficients is non-zero OThere is insufficient evidence to support the claim that all of the regression coefficients are equal to zero 00
Expert Solution
Step 1

Given:

Number of predictor variables k=5

sample size n=36

Degrees of freedom:

The degrees of freedom for regression is calculated below:

df(Regression)=k=5

Thus, the degrees of freedom for regression is 5

The degrees of freedom for residuals is calculated below:

df(Residuals)=n-(k+1)=n-k-1=36-5-1=30

Thus, the degrees of freedom for residuals is 30

The degrees of freedom for total is calculated below:

df(Total)=n-1=36-1=35

Thus, the degrees of freedom for total is 35

Step 2

Sum of Squares:

The sum of squares for regression is calculated as below:

SS(Regression)=MS(Regression)×df(Regression)=25×5=125

Thus, the sum of squares for regression is 125

The sum of squares of Total is calculated as below:

SS(Total)=SS(Regression)+SS(Residual)=125+398=523

Thus, the sum of squares of Total is 523

Mean sum of squares:

The Mean sum of squares for residual is calculated as below:

MS(Residual)=SS(Residual)df(Residual)=39830=13.267

Thus, the Mean sum of squares for residual is 13.267.

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