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.
- 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.
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|
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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