I have a basic understanding of basic statistics, but I believe I've gotten myself out of my depth.
I have a data set with a dependent variable (time span) and three quantitative independent variables. There is also a qualitative independent variable (a type flag) but I think I can quantify it if I must. The quantitative independent variables all seem to be inversely proportional to the dependent variable.
I want to see if I can determine which of these independent variables has the most influence over the dependent. I ran all data through regression tests using
statsmodels for Python (ordinary least squares) but I get warnings indicating multicollinearity and $R^2 = 0.002$. I've also tried univariate linear regression of each independent but am not getting something that looks usable.
Finally, I also have this problem of the qualitative independent.
Again, I'd really like to know how these independents work together to influence the dependent, and I'd also like to know the degrees to which they influence but I'm clearly lost as to the methodology.
1 The condition number is large, 5.65e+06. This might indicate that there are strong multicollinearity or other numerical problems.
Screenshot of full output from
I should also note that two of these independent variables (
buffercount) repeat for every combination of
diskconfig (<- this is the qualitative variable, and I think I have a way of quantifying that now).
backup_time_ms is the dependent variable.