According to the statistical data, analyze and explain which tables describe how

Question

According to the statistical data, analyze and explain which tables describe how does old age and gender predict loneliness? Please be specific as possible.

Regression Descriptive Statistics Mean Std ne grow_old female Std. Deviation 983 496 452 2.06 166 166 166 72 Correlations lonely grow old female 030 030 1.000 353 352 Pearson Correlation lonely 1.000 .158 030 .158 1.000 .030 021 grow old female lonely grow old female lonely grow old female Sig. 1-tailed) 021 353 166 166 166 352 166 166 166 166 166 166 Variables Entered/Removeda Variables Entered Variables Removed Model Method female row old Enter a. Dependent Variable: lonely b. All requested variables entered

Explanation / Answer

From table of coefficients the estimated regression equation is

Loneliness=2.294-0.315*grow_old-0.075*female

ANOVA table showed that the overall regression model is not significant with F(2,163)=2.19, p=0.115>0.05. R2 is 0.026 which means that grow_old and femae explain only 2.6% variations in loneliness. The coefficient of grow_old is significant with p=0.041<0.05 . Hence, holding gender fixed corresponding to one year increase in age there is on an average a decrease of 0.315 in loneliness. However, female/gender is not a significant predictor of loneliness as p=0.658>0.05.

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