the scores are dependent. It's talking about a subset of the data compared to the entire set, rather than a similar subset or random set. The term unlabeled R

the scores are dependent. It's talking about a subset of the data compared to the entire set, rather than a similar subset or random set. The term unlabeled Random_Race is the same as Random_Race:score_factorHigh+score_factorMedium, as opposed to each one individually. So while neither high nor medium alone have statistical significance for African Americans, together they do, a statistical puzzle. Or rather, if you had also copied line 44, less of a puzzle, since `score_factorWhatever` becomes significant in a race specific model. It isn't race alone nor the score alone. It is something else (age? another not modeled thing?) They say so in this link, https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm https://www.propublica.org/article/how-we-analyzed-the-compa... Where they explain a bit more in detail what the chart labels mean than what they are labeled in the R script. Score == dependent variable. So why you ran your blog comments as Score == potential independent variable is a little strange. As for why you want to critique the very last chart (which does appear in 36, and does as a big chart not to work at all) Who cares? Overall, every other time, if we look at a Pearsons fit (line 51) All defendants Low High Survived 2681 1282 0.55 Recidivated 1216 2035 0.45 Total: 7214.00 False positive rate: 32.35 False negative rate: 37.40 Specificity: 0.68 Sensitivity: 0.63 Prevalence: 0.45 PPV: 0.61 NPV: 0.69 LR+: 1.94 LR-: 0.55 Why the hell would we use this for sentencing guidelines? It isn't very specific, nor sensitive. It has a fairly high false positive and false negative rate. When you jail someone, you take away that person's rights and you are probably as much as not going to jail them again. This sentencing guideline basically disguises that, and does it in such a way where it isn't specific nor sensitive, and to boot, 1/3 of the time you'll be wrong in your decision. Furthermore, you'll already know in your gut which 1/3 it is going to be - probably someone young or black. Propublica's writers are totally justified to write the article. They go further than many journalists and show you what they did, and there is no rule in the 4th estate that says they have to do that. If you don't like the fact that statistics as a subject, and policies dependent on statistics, for most people, have to be framed with a story, that's a different issue altogether. But why not come out and just say that.