Regression can be used to predict variables:
- IV: x axis (predictor)
- DV: y axis (criterion / outcome)
Analyze -> Regression -> Linear
- move variables into corresponding boxes
- ensure “Method = Enter”
- in SPSS
- raw equation: DV = (B [slope] x IV) + constant [intercept]
- standardised: ZDV = β [beta] x ZIV (standardised variables to Z scores)
- standardised is a better indicator of strength and measure independent of units
- in multiple regression (more than one IV) β measures unique effect of IV – no shared variance
- look in last table for β value (the correlation) and B and constant
- look in ‘model summary’ table for R2 (proportion of variance explained by all IVs)
- look in ‘ANOVA’ table for F value (to check if R2 predicts DV better than chance – if F is significant then R2 is better)
- R2: need to multiply by 100 to get %