Assignment:
Q1: Sethi and Seligman (1993) examined the relationship between optimism and religious conser¬vatism by interviewing over 600 subjects from a variety of religious organizations. We can regress Optimism on three variables dealing with religiosity. These are the influence of religion on their daily lives (Rellnf), their involvement with religion (Rellnvol), and their degree of religious hope (belief in an after-life) (RelHope). The results arc shown as SPSS printout.
Model Summary
Adjusted Std. Error of
Model R R Square R Square the Estimate
1 .321a .103 .099 3.0432
a. Predictors: (Constant), relined, rani, relhope
ANOVAb
Sum of Mean
Model Squares df Square f Sig.
1 Regression
Residual Total 634.240 5519.754 6153.993 3 596 599 211.413
9.261 22.828 .0004
a. Predictors: (Constant), relinvol, rani, relhope L Dependent Variable: optimism
Coefficientsa
Unstandardized Standardized Coefficents Coefficients
Model B Std. Error Beta t Sig. Tolerance
I. (Constant) -1.895 512 -3.702 .000
relhope .428 .102 .199 4.183 000 .666
relief .490 .107 .204 4.571 .000 .755
relinvol -.079 .116 -.033 -.682 .495 .645
Dependent Variable optimism
Looking at the preceding printout,
(a) Are we looking at a reliable relationship? How can you tell?
(b) What is the degree of relationship between Optimism and the three predictors?
(c) What would most likely change in your answers to (a) and (b) if we had a much smaller number of subjects?
Q2 In Q1 which variables make a significant contribution to the prediction of Optimism as judged by the test on their slopes?
Q3 In Q1 the column headed 'Tolerance" (which you have not seen before) gives you 1 minus the squared multiple correlation of that predictor with all other predictors. What can you now say about the relationships among the set of predictors?
Q4 On the basis of your answer to Q3, speculate on one of the reasons why Religious Influence might be an important predictor of Optimism, white Religious Involvement is not.