Correlation Analysis for Surveys
From a statistical perspective, we have to make one disclaimer. Correlation cannot determine cause and effect. Strictly speaking, correlation can only indicate the strength of the statistical relationship between two survey questions. It cannot indicate which of those items is influencing the other item. (And in some cases, there could even be a third, unmeasured factor that is the real cause of the observed correlation between two survey items.)|
For example, take the item related to job stress and anxiety. There is no way to say for sure that employee satisfaction is a result of low stress, or the other way around - that low stress is a result of employee satisfaction.
If you are feeling brave and you want to better understand correlation and causation, see Wikipedia's synopsis.
Within the context of an employee satisfaction survey or an employee engagement survey, we take a more
Correlations (r) significant at p < 0.05. This is a customary indication of the likelihood that the observed correlations are a result of chance. For our purposes, we have set this probability (p) threshold to be no more than 0.05 or 5%. There is less than a 5% likelihood that the correlations listed here are a result of chance.Whenever you view correlations, it is important to look for this p-level. You don't need to understand more about it than is explained here. Just know that "p < 0.05" is the most common standard threshold for statistical significance.