The following output is from a multiple regression analysis that was run on the variables FEARDTH (fear of death) IMPORTRE (importance of religion), AVOIDDTH (avoidance of death), LAS (meaning in life), and MATRLSM (materialistic attitudes). In the regression analysis, FEARDTH is the criterion variable (Y) and IMPORTRE,AVOIDDTH, LAS, and MATRLSM are the predictors (Xs). The SPSS output is provided below, followed by a number of questions.  Descriptive Statistics   Mean Std. Deviation N feardth 27.0798 8.08365 163 importre 5.8282 2.46104 163 avoiddth 18.5460 6.97633 163 Las 70.1288 9.89460 163 matrlsm 53.5552 10.21860 163   Model Variables Entered Variables Removed Method 1 matrlsm, avoiddth, importre, lasa   . Enter   a. All requested variables entered. b. Dependent Variable: feardth                                     Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .669 .447 .433 6.08700   Predictors: (Constant), matrlsm, avoiddth, importer, las   ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 4731.810 4 1182.952 31.927 .000a Residual 5854.153 158 37.052     Total 10585.963 162       a. Predictors: (Constant), matrlsm, avoiddth, importre, las b. Dependent Variable: feardth Coefficients: Model Unstandardized Coefficients Standardized Coefficients T Sig. B Std. Error Beta 1 (Constant) 27.738 4.979   5.571 .000 importre -.167 .199 -.051 -.838 .403 avoiddth .697 .070 .601 10.004 .000 Las -.213 .050 -.261 -4.247 .000 matrlsm .044 .049 .055 .885 .378 a. Dependent Variable: feardth 1. Is R2 significant? Report the appropriate statistical criteria (including the R2, F, df, and p-value) to support your answer Which predictor(s), if any, are significant? Which predictor(s), if any, are not significant? Be sure to (1) indicate whether each predictor is significant or not and (2) report the corresponding t values and p-values for each of the predictors (whether significant or not) below. Write the final equation for the regression model.

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  1. The following output is from a multiple regression analysis that was run on the variables FEARDTH (fear of death) IMPORTRE (importance of religion), AVOIDDTH (avoidance of death), LAS (meaning in life), and MATRLSM (materialistic attitudes). In the regression analysis, FEARDTH is the criterion variable (Y) and IMPORTRE,AVOIDDTH, LAS, and MATRLSM are the predictors (Xs). The SPSS output is provided below, followed by a number of questions. 

Descriptive Statistics

 

Mean

Std. Deviation

N

feardth

27.0798

8.08365

163

importre

5.8282

2.46104

163

avoiddth

18.5460

6.97633

163

Las

70.1288

9.89460

163

matrlsm

53.5552

10.21860

163

 

Model

Variables Entered

Variables Removed

Method

1

matrlsm, avoiddth, importre, lasa

 

.

Enter

 

a. All requested variables entered.

b. Dependent Variable: feardth

 

                                  Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.669

.447

.433

6.08700

 

  1. Predictors: (Constant), matrlsm, avoiddth, importer, las

 

ANOVA

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

4731.810

4

1182.952

31.927

.000a

Residual

5854.153

158

37.052

 

 

Total

10585.963

162

 

 

 

a. Predictors: (Constant), matrlsm, avoiddth, importre, las

b. Dependent Variable: feardth

Coefficients:

Model

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

B

Std. Error

Beta

1

(Constant)

27.738

4.979

 

5.571

.000

importre

-.167

.199

-.051

-.838

.403

avoiddth

.697

.070

.601

10.004

.000

Las

-.213

.050

-.261

-4.247

.000

matrlsm

.044

.049

.055

.885

.378

a. Dependent Variable: feardth

1. Is R2 significant? Report the appropriate statistical criteria (including the R2, F, df, and p-value) to support your answer

Which predictor(s), if any, are significant? Which predictor(s), if any, are not significant? Be sure to (1) indicate whether each predictor is significant or not and (2) report the corresponding t values and p-values for each of the predictors (whether significant or not) below.

Write the final equation for the regression model. 

 

 

 

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