I'm working on a project where I'm analyzing how improvements in players' skills are associated with changes in their values. Specifically to see if there is a correlation between point changes in certain skills and percent changes in their value.
I used .corr() and p-values (<.01) for those calculated correlation coefficients to find a set of skills that have a correlation coefficient > .5 (moderate to high correlations). So this would be correlations for each individual skill to percent change in value.
I then decided to explore the data set with LinearRegression() from scikit-learn and found regression coefficients that are totally different for those same skill variables correlation coefficients I have found (in that they're negative and much smaller, ie correlation coefficient for attacking: 0.51, regression coefficient for attacking: -0.079).
I'm new to this, but does that seem plausible? Or did I possibly make a mistake in calculations? It doesn't make sense for a positive correlation to have a negative regression coefficient.
sklearn
automatically used regularization. Check out if that is still the case. If it is, perhaps trystatsmodels
. $\endgroup$ – Dave Sep 23 '20 at 21:13