PSY 302 Lecture Notes - Lecture 20: Statistical Significance, Electroencephalography
Document Summary
Spss will say that it is zero when in reality it is some decimal out to zero. Summary of multiple regression analysis for variables predicting subjective pain. Burn severity, epinepherine levels, and eeg, gsr, and pfi scores were used to predict subjective ratings of pain in a multiple regression analysis. The results of this analysis are shown in table 1. The overall regression model was statistically significant, with the predictors explaining 51. 8% of the variance in subjective pain ratings, f (5, 324) = In the context of the other predictors, burn severity and gsr scores did not emerge as statistically significant predictors of subjective pain. In the context of the other predictors, higher levels of subjective pain were statistically significantly related to higher epinepherine levels and lower eeg and pfi scores. While gsr scores were not statistically significant predictors of subjective pain in the context of the other variables, gsr scores and subjective pain did have a strong zero-order correlation.
