Page 142 - Quantitative Data Analysis

Quantitative Data Analysis
Simply Explained Using SPSS

SPSS output for Simple Regression

Model Summary

Model R R Square Adjusted R Std. Error of
Square the Estimate
a
1 .408 .167 -.111 .94281
a. Predictors: (Constant), Sleep

Model summary provide descriptive statistics about regression that
includes correlation value, R squared (Coefficient of determination)
and adjusted R-square and error estimation. According to model
summary the correlation is 0.408 (Please note this is negative
number as we have already calculated above). The R-square is .167
which means that 16.7% of variation in stress is due to hours of
sleeping. R-squared indicates that how strong the predictor is.

a
ANOVA
Model Sum of df Mean F Sig.
Squares Square
b
Regression .533 1 .533 .600 .495
1 Residual 2.667 3 .889

Total 3.200 4
a. Dependent Variable: Stress
b. Predictors: (Constant), Sleep

The Theory and Applications of Statistical Inferences 126