Question

Linear regression analysis of the data revealed the following: Model Summary Model R R Square Adjusted...

  1. Linear regression analysis of the data revealed the following:

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.695a

.483

.478

13.02473

a. Predictors: (Constant), exercise, gender, subject's age, depressed state of mind

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

65230.870

4

16307.718

96.129

.000b

Residual

69893.149

412

169.644

Total

135124.019

416

a. Dependent Variable: Life Purpose and Satisfaction

b. Predictors: (Constant), exercise, gender, subject's age, depressed state of mind

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

100.074

3.380

29.609

.000

93.430

106.718

gender

3.766

1.350

.099

2.789

.006

1.112

6.420

subject's age

.115

.050

.081

2.276

.023

.016

.214

depressed state of mind

-15.575

.918

-.617

-16.975

.000

-17.379

-13.772

exercise

3.203

.641

.182

4.997

.000

1.943

4.464

a. Dependent Variable: Life Purpose and Satisfaction

  • When controlling for all other variables, is there any variable that is NOT a significant predictor of Life Purpose and Satisfaction?

  • By how much does Life Purpose and Satisfaction decline for each incremental worsening in depressed state of mind when controlling for gender, age, and exercise?

  • Other factors being equal (gender, depressed state of mind, exercise), does Life Purpose and Satisfaction improve with age? If yes, by how much each year?

  • Based on the GLM, what would the predicted Life Purpose and Satisfaction score be for a 60 year-old woman who rarely exercises and often feels in a depressed state of mind?

0 0
Add a comment Improve this question Transcribed image text
Answer #1

When controlling for all other variables, is there any variable that is NOT a significant predictor of Life Purpose and Satisfaction

All variables are significant.

--------------------------------------

By how much does Life Purpose and Satisfaction decline for each incremental worsening in depressed state of mind when controlling for gender, age, and exercise.

-15.575

-----------------------------

Other factors being equal (gender, depressed state of mind, exercise), does Life Purpose and Satisfaction improve with age.

Yes it been increased with Age.

.115 increase for every 1 increase in age.

-----------------------------------------

Based on the GLM, what would the predicted Life Purpose and Satisfaction score be for a 60 year-old woman who rarely exercises and often feels in a depressed state of mind.

= 91.399 (When consided Female = 0)

= 95.165(When consided Female = 1)

Thanks in advance!

revert back for doubt

Please upvote


Add a comment
Know the answer?
Add Answer to:
Linear regression analysis of the data revealed the following: Model Summary Model R R Square Adjusted...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • QUESTION 6 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate...

    QUESTION 6 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .641a .410 .406 4.507 a. Predictors: (Constant), age 3 groups, Total Mastery, Total Optimism Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 50.016 1.409 35.508 .000 Total Mastery -.786 .067 -.526 -11.719 .000 Total Optimism -.217 .060 -.164 -3.623 .000 age 3 groups -.712 .275 -.098 -2.588 .010 a. Dependent Variable: Total perceived stress What proportion of...

  • Model Summary Adjusted R Square Std. Error of the Estimate Model R R Square 1 .843a...

    Model Summary Adjusted R Square Std. Error of the Estimate Model R R Square 1 .843a .711 .707 7.812812 a. Predictors: (Constant), Fuel efficiency, Horsepower Coefficientsa Standardized Coefficients Beta Sig 2.354 .020 Unstandardized Coefficients Model B Std. Error 1 (Constant) 28.144 11.954 Horsepower 229 .013 Length - 219 Fuel efficiency -.090 .185 a. Dependent Variable: Price in thousands .906 16.989 ,000 .050 - 205 -4.348 .000 -.027 -.488 .627 Model Summary Adjusted R Square Std. Error of the Estimate Model...

  • Models 1-7 are below Part C: Select one model you would use to explain reading ability.,Then use that model to find the 95% confidence interval estimate for the mean reading ability 95% p...

    Models 1-7 are below Part C: Select one model you would use to explain reading ability.,Then use that model to find the 95% confidence interval estimate for the mean reading ability 95% prediction interval for reading ability When age 6, mem span 4.2 and ig 91. Regression [DataSetll C:\Usersn.little5773 Downloads\child data.sav Variables Entered/Removed Variables Entered Variables Removed Method Model Enter age a. Dependent Variable: reading ability b. All requested variables entered. Model Summary Adjusted R Square Std. Error o R...

  • Model Summary Change Statistics Adjusted Std. Enor of R Square Model R R Square Square the Estimate 657 432 29042057161...

    Model Summary Change Statistics Adjusted Std. Enor of R Square Model R R Square Square the Estimate 657 432 2904205716161 4 32 a. Predictors: (Constant, eigencentrality, Average 15All optimice_threshold_b F Changed 3.0393 Sig F Change .071 12 ANOVA Sig 071 Sum of Model Squares Mean Square Regression 1.612 537 3.099 Residual 2.12) 12 Total 3.735 a Dependent Variable: average_MSEMSE b. Predictors: (Constant. eigencentrality Average 15Aoptimized_threshold_b Coefficients Standardized Coeficients Beta Collinearity Stanisses Tolerance Model Sia 000 Unstandardized Coeficients B Sid Error...

  • Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .884a...

    Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .884a .782 .775 1134.08895 a. Predictors: (Constant), Tuition2000 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1133.148 701.455 1.615 .116 Tuition2000 1.692 .160 .884 10.551 .000 a. Dependent Variable: Tuition2008 What is the regression equation? What is the percent of variation in BMI explained by the regression line? Predict 2008 Tuition for Oregon given their 2000 tuition rate. Predict...

  • Regression Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Warranty_Yearsb . Enter a. Dependent Variable:...

    Regression Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Warranty_Yearsb . Enter a. Dependent Variable: Number_of_people_mentioned b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .503a .253 .251 .95930 a. Predictors: (Constant), Warranty_Years ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 80.590 1 80.590 87.574 .000b Residual 237.425 258 .920 Total 318.015 259 a. Dependent Variable: Number_of_people_mentioned b. Predictors: (Constant), Warranty_Years Coefficientsa Model Unstandardized...

  • Hello, appreciate if anyone could help me on Multiple Regression analysis. Thanks! Question 4 Use the...

    Hello, appreciate if anyone could help me on Multiple Regression analysis. Thanks! Question 4 Use the multistep process to interpret the regression result below. This model has been run by a researcher trying to explain user pleasure of browsing Facebook. The independent variables are user perceptions of Perceived Usefulness, Complementary Convenience and Entertainment. Model Summary Change Statistics Std. Error R of the Adjusted R R Sig. F Change Model R df2 df1 Square Change Square Estimate Change Square 392 .097a...

  • Overview of the Study: The data are based on a Comprehensive School Reform (CSR) Initiative that...

    Overview of the Study: The data are based on a Comprehensive School Reform (CSR) Initiative that focused on the improvement of reading and writing for students in the primary grade. The school received a grant from the state which was used to strengthen classroom teachers’ instructional skills. The regression outputs present information for students in the school. Description of the variables: Please use the following description/coding to help you in your analyses. Gender: female; 1 male=0 Coding – Gender female...

  • Refer to Exhibit A-1. State four (4) assumptions of the linear model. Refer to Exhibit A-1....

    Refer to Exhibit A-1. State four (4) assumptions of the linear model. Refer to Exhibit A-1. Identify the dependent and independent variables in the model and indicate their levels of measurement. Refer to Exhibit A-1. What is the difference between the R-square and adjusted R-square in the output? Refer to Exhibit A-1. State the null and alternative hypotheses of the test presented in the output. Exhibit A-1: Depending on the type of work one is planning, its complexity, and how...

  • Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted...

    Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted R Square 0.477366 Standard Error Observations 14 ANOVA df SS MS F Regression 1 3.028885709 Residual 12 2.823257148 Total 13 5.852142857 Coefficients Standard Error t Stat P-value Intercept 1.157091 0.566482479 0.063699302 Satisfaction with Speed of Execution 0.636798 0.177478218 0.003726861 Group of answer choices R Square is 0.517 Standard error is 0.386 Residuals are 2.823 F-test is 11.87 R Square is 0.517 Standard error is...

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT