Apparently, age accounts for .4356 (.66^2) of the variance of the scores.
Use chi-square with cells for age and gender.
Example: Relation between height and level of executives for males was significant, with greater height indicating higher level (statistical significance). However, the differences were only in fractions of an inch, not allowing much prediction of executive level (substantive significance).
I have recently administered an employee survey at a call center. I found a Pearson r of -.66 between the employees' ages and their scores on an employee engagement scale. What does this finding represent/mean? Also, there is a relationship between gender and employee engagement (chi-square was statistically significant at p<.05. I do I now perform an analysis that incorporates both gender and age in predicting employee engagement? Plus how do statistical significance and substantive (or meaningful) significance differ?
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1 answer