Well I finally understand what a QQ plot is showing, awesome! Quick question - why would you choose say a 25-7th percentile reference line as opposed to a regression line? What influences that decision and what impact does that decision have on evaluation? Also - what is the reference line generated by default in say R or python?
Considering the regression fit as the reference line can be influenced by outliers. That is why we prefer the line connecting 25-75th percentile. I am not sure about R but in Python, we must specify the parameter when creating a QQ plot, i.e., there is no default value: https://www.statsmodels.org/stable/generated/statsmodels.graphics.gofplots.qqplot.html
Always an informative read!
Great as always!
Very interesting and applicable concepts in every blog. Thank for share!
Very well explained. Thank you
Well I finally understand what a QQ plot is showing, awesome! Quick question - why would you choose say a 25-7th percentile reference line as opposed to a regression line? What influences that decision and what impact does that decision have on evaluation? Also - what is the reference line generated by default in say R or python?
Considering the regression fit as the reference line can be influenced by outliers. That is why we prefer the line connecting 25-75th percentile. I am not sure about R but in Python, we must specify the parameter when creating a QQ plot, i.e., there is no default value: https://www.statsmodels.org/stable/generated/statsmodels.graphics.gofplots.qqplot.html