Hi guys,

I am not too experienced with statistics, but am conducting some quantitative analysis for my undergrad Psychology dissertation and would like a bit of help please.

I ran a linear regression to see if social support level (a binary variable - either low or high) could predict Total Difficulties Score (a continuous variable). But, when running my assumptions test, the assumption of homoscedasticity was violated. Therefore, I did some research and found that one way of overcoming this problem is by log transforming the dependent variable. So, I log transformed Total difficulties score, creating a new variable called log_totaldifficultiesscore. I then reran the regression and the assumption was no longer violated, so the problem was overcome. BUT, I am know unsure as to HOW to interpret the coefficients, as it is no longer RAW scores being discussed in the regression but LOG TRANSFORMED SCORES. So, what would a coefficient of -.370 actually mean? Or, how can I can I 'un-log transform' the coefficients??

I hope my explanation makes sense and someone can help, I have been struggling with this for a few days now!

Thank you