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Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .972a .945 .933 .860 a. Predictors: (Constant), Importance, Duration ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 114.264 2 57.132 77.294 .000b Residual 6.652 9 .739 Total 120.917 11 a. Dependent Variable: Attitude b. Predictors: (Constant), Importance, Duration Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .337 .567 .595 .567 Duration .481 .059 .764 8.160 .000 Importance .289 .086 .314 3.353 .008 a. Dependent Variable: Attitude Q 1. What r signifies in the model summary? (2 pts) Q 2. How do you explain r square in the Model Summary? (3 pts) Q 3. What does that Sig. .000 tell us in ANOVA table and how do you read DF in the table? (2 pts) Q 4. How do you describe coefficients table here? (3 pts)

          Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .972a .945 .933 .860
a. Predictors: (Constant), Importance, Duration

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 114.264 2 57.132 77.294 .000b
Residual 6.652 9 .739
Total 120.917 11
a. Dependent Variable: Attitude
b. Predictors: (Constant), Importance, Duration

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) .337 .567 .595 .567
Duration .481 .059 .764 8.160 .000
Importance .289 .086 .314 3.353 .008
a. Dependent Variable: Attitude

Q 1. What r signifies in the model summary? (2 pts)
Q 2. How do you explain r square in the Model Summary? (3 pts)
Q 3. What does that Sig. .000 tell us in ANOVA table and how do you read DF in the table? (2 pts)
Q 4. How do you describe coefficients table here? (3 pts)

Show more…

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .972a .945 .933 .860
a. Predictors: (Constant), Importance, Duration

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 114.264 2 57.132 77.294 .000b
Residual 6.652 9 .739
Total 120.917 11
a. Dependent Variable: Attitude
b. Predictors: (Constant), Importance, Duration

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) .337 .567 .595 .567
Duration .481 .059 .764 8.160 .000
Importance .289 .086 .314 3.353 .008
a. Dependent Variable: Attitude

Q 1. What r signifies in the model summary? (2 pts)
Q 2. How do you explain r square in the Model Summary? (3 pts)
Q 3. What does that Sig. .000 tell us in ANOVA table and how do you read DF in the table? (2 pts)
Q 4. How do you describe coefficients table here? (3 pts)

Added by Tyler T.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

Instant Answer

Solved by Expert Madhur L

10/06/2023

Step 1

The Model Summary provides information about the overall performance of the regression model. In this case, the R Square value of 0.972 indicates that 97.2% of the variance in the dependent variable (Attitude) can be explained by the independent variables Show more…

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Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .972a .945 .933 .860 a. Predictors: (Constant), Importance, Duration ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 114.264 2 57.132 77.294 .000b Residual 6.652 9 .739 Total 120.917 11 a. Dependent Variable: Attitude b. Predictors: (Constant), Importance, Duration Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .337 .567 .595 .567 Duration .481 .059 .764 8.160 .000 Importance .289 .086 .314 3.353 .008 a. Dependent Variable: Attitude Q 1. What r signifies in the model summary? (2 pts) Q 2. How do you explain r square in the Model Summary? (3 pts) Q 3. What does that Sig. .000 tell us in ANOVA table and how do you read DF in the table? (2 pts) Q 4. How do you describe coefficients table here? (3 pts)

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00:01 Hello students, in this question we have given the model summary and the anova table for the regression and by using that we have to solve the following questions.

00:10 Now in the first question, we have to explain what r signifies in the model summary.

00:16 So now capital r signifies signifies the multiple correlation coefficient, the multiple correlation coefficient and in the simple linear regression in the simple linear regression correlation coefficient correlation coefficient that is r signifies signifies the measure of the relationship the measure of the relationship relationship between the independent variable that is x and the dependent variable y.

01:24 However, a multiple correlation coefficient gives us the measure of the strength of the relationship between the observed values and the best predicted values of the dependent variable of y.

01:36 Therefore here r signifies the correlation between the observed values of attitude and the best predicted value of attitude which is predicted using importance and duration as the predictors.

01:48 Then in the second question, we have to explain how do you explain r square in the model summary.

01:54 So now we know that r square tells us that the amount of variation in the dependent variable explained by the independent variable and here we have the value of r square is equal to 0 .945 which means that 94 % of the variability 94 % of the variability in the dependent variable that is in the attitude attitude is explained by is explained by the independent variables, which are importance by importance and the duration.

02:52 So this is the interpretation of the r square...

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