My god! It is almost as if someone could modify their opinion on something over four years…
It’s reasonable to interpret iiandyiiii’s position as unchanged based on posts in this thread.
Which ones in this thread? Assuming you’re talking about the shooting disparity numbers, I looked back and I alluded to my own lack of certainty multiple times. Not that I think I was certain in the other thread, either.
What he as modified is his standards of evidence. Pro-Publica’s statistical observation was enough to be damning but two peer reviewed studies are merely a counterpoint.
People thought saying that Trump would be our next POTUS was ridiculous and hilarious too.
Just wait until iiandyiiii declares martial law “for our own good”
I think it would be great that a member of the government out there has the power to declare martial law, and in his free time, posts on this message board.
*** starts scouring the government rosters for people named “Andrew”
The response was “nuh uh” and even if they are, I’m cool with it because there is no real societal harm.
Sometimes I have to just let people be wrong. Its particularly hard on the internet.
First let me apologize for taking so long between posts. Since the thread isn’t titled “Statistical analysis of Police shootings” I forget to check it. Second, I’m mostly just reading Damuri Ajashi’s comments on my posts so if I missed something that has already been covered previously in the thread I further apolgize.
No what I am saying is that they did a subset analysis that resulted in a result so significant that it didn’t matter whether they data dredged or not. Perhaps and example of what is or is not data dredging might be useful.
Suppose I was doing a study of lead levels in children and I report that “Dreadville California has a lead level in its children that is 2 times the national average with a p-value of 10^-5 (one chance in 100,000 that this could have happened by chance)” On its own that would seem to indicate that there was something wrong with Dreadville. But if it was later pointed out that Dreadville was to top city of 70,000 cities that I had looked at, then it becomes less interesting. I rolled that dice 70,000 times and one time I got a very high results, purely by chance this would have occurred 70% of the time. Dreadville just happened to be the (un)lucky one. This is an example of data dredging.
But suppose instead I reported “Flint Michigan has a lead level 20 times the national average with a p-value of 10^-16”. Then we have a different story even if I rolled the dice 70,000 times there is no way I would be able to get a result this high purely by chance. There must be something different going on in Flint that makes its lead levels so high. Now this result would only apply to Flint and doesn’t say anything in particular about the rest of the Detroit Metro area. In fact it might be that Grosse Pointe Shores has a level of lead poisoning that is significantly lower than the national average with a very significant p-vlaue. That is a different headline which in no way disputes what was found in Flint.
The Pro publica analysis fits more in this latter category. With the added proviso that given the strong notion in society that young black men are thugs, there is a compelling reason to concentrate on this group.
Incidentally data dredging and cherry picking is my bread and butter. I analyze genetic data that involves looking at tens of thousands of genes to find the ones that are likely to be important. Those at the top of the list always look great, and its hard to convince the biologists, (who can always make a compelling story after the fact as to why this makes perfect sense) that these are just random noise. But if there is something in the data it will come out from picking a few strong results out of tens of thousands of garbage. The key is to be able to tell the difference.
Sorry I was trying to combine my explanation with a bit of a statistics tutorial for those that were interested and no something of the subject. Long story short, the worst case scenario there could be around 3,000 possible cuts of the data (3,160 rolls of the dice) so we could multiply our p-value by 3,160. However many of these would result in subsets that have no chance of ever producing a significant result because the subsets are too small, and also many of those that remain are highly correlated since they include many of the same shootings. So in fact the actual amount that the p-value should be adjusted is probably much less than 3,160.
Sorry must have missed it in skimming. Given that the ratio of blacks to whites 1 to 3.54 we would only expect about 2 black so that we found 0 is low but not out of the realms of probable chance. Even without any adjustments due to the multiple comparisons you admit to, we get a p-value of .175 or a little more than one chance in 6. The 95% confidence interval for ratio of blacks to white being shot is (0-1.44) on this data meaning that if this was the only data you looked at, you could be pretty sure that the ratio between blacks to whites in this age group was less than 1.44 to 1. But since this was cherry picked, the results may be biased.
Its possible, but I see no reason that it is necessarily so and even if it was its not enough to fully explain their results.
Well, I guess I should say that after the two studies, the calculation didn’t need to be made. It was fine to throw numbers around and stab in the dark before we had any real facts.
Yes, there is a difference if you ignore all other variables. Hell you don’t need to cherry pick the data to see statistically significant differences. The confidence interval is even better when you look at ALL the data. Peer reviewed studies saw these differences and they say that the difference is basically illusory. When comparing like to like, there is no difference between blacks and whites.
Do you dismiss those studies in favor of the pro-publica bullshit as well? Or even put the Pro-Publica factoid on the same level as those peer reviewed studies?
And do you really consider what Pro-Publica did to be a “study”?
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I would say that the Pro-Publica was a subset analysis of another study that demonstrated that there was a subset of the data, namely those between the ages of 14-19, that had a much higher discrepancy between blacks and whites than was present in the data as a whole.
Too late to edit:
when doing the 6 vs 0 old age confidence interval I forgot to account for the larger number of blacks to whites in the population, and then whether I was doing white/black or black/white. :smack:
The confidence interval should actually be (0-1.86) with no accounting for cherry picking. If Damuri Ajashi looked at around 10 independent sets before settling on this one as the best, than the confidence interval might increase to be around (0-2.6).
Another wonderfully dangerous post, Buck! Kudos on your dangerousness!
But you are not comparing the death rate of black youth from 14-19 with the death rate of all blacks. You are comparing it to what you would have in the absence of any disparity. IOW aren’t you increasing the disparity by a factor of 3.
At what point do you consider a subset to be too small? I mean we are looking at a subset of less than 2% here and its big enough but at .2% its not.
Here you are referring to the Pro-Publica “study” as “calculations”? You are saying that Pro-Publica was throwing numbers around and stabbing in the dark, which is fine when there is nothing else to go by?
Just wanted to point this out because iiandyiiii seems to have read only the 4 sentences in your post that he thinks helps him.
Once again, aren’t you increasing the discrepancy by a factor of three? I mean the data as a whole already has a 3::1 discrepancy.
/taps iiandyiiii on the head
“Well, I guess I should say that after the two studies, the calculation didn’t need to be made. It was fine to throw numbers around and stab in the dark before we had any real facts.”
“Peer reviewed studies saw these differences and they say that the difference is basically illusory. When comparing like to like, there is no difference between blacks and whites.”
If I understand him correctly, he is basically saying that my hypothesis that this was cherrypicking is STILL unlikely given how dramatically the subset of 54 diverges from parity (I still think he should be comparing it to the dataset as a whole (3::1) but I don’t do it for a living so I will defer to him). However peer reviewed studies makes those ad hoc calculations made by pro-publica interesting but irrelevant.
“Well, I guess I should say that after the two studies, the calculation didn’t need to be made. It was fine to throw numbers around and stab in the dark before we had any real facts.”
“Peer reviewed studies saw these differences and they say that the difference is basically illusory. When comparing like to like, there is no difference between blacks and whites.”
If I understand him correctly, he is basically saying that my hypothesis that this was cherrypicking is STILL unlikely given how dramatically the subset of 54 diverges from parity (I still think he should be comparing it to the dataset as a whole (3::1) but I don’t do it for a living so I will defer to him). However peer reviewed studies makes those ad hoc calculations made by pro-publica interesting but irrelevant. Notice how he doesn’t call it a study like you do? Probably because its not.
And there is nothing dangerous about Buck Godot and his facts. And as your credibility is slowly being undermined, you are also becoming less dangerous, pretty soon you will just be another partisan hack, a polite one, but just another partisan hack nonetheless. The reason I think you are dangerous is not because your ideas are dangerous, they are not, they are mundane.
What makes you dangerous is that people get fooled into agreeing with you because of how agreeable you seem to be. I mean how much more agreeable can you get than to say “well you have some stuff (2 peer reviewed studies and I have some stuff (a calculation made by a partisan organization), can’t we agree that there is room for disagreement?”
What you are doing is injecting undue uncertainty into something that is reasonably well established. If a more transparent partisan hack proposed these things, people would just chuckle and ignore them. You are sort of like someone who points to some factoids published by the Petroleum Institute of America on the one hand and peer reviewed studies on the other and saying “hey lets teach the controversy”
You don’t go where the facts lead you unless you want to go there in the first place, in all other cases you can’t seem to find the map.
Wonderful job quoting yourself from post #260! Buck appeared to miss a quote tag, but those are your exact words that you quoted (seriously – both of those quotes are your own exact words. Check the tape!). Quoting your own non-professional argument to support your opinion must be very convincing to you. Alas, it’s not terribly convincing to me.
Maybe my danger is rubbing off on you. Quoting yourself to support your opinion sounds like just the kind of dangerous post you’re afraid of!
Hmm that’s a weird double post. Ignore post 292 and stick with post 293.
Yes, I’ll keep giggling about how triumphant you must feel after quoting your own exact words! Keep it up… dangerously! 
Damn good point. Lets see if Buck Godot will come back and actually answer the question then.
In light of two subsequent studies, how relevant is the pro-publica analysis?
Okay, I’ll try to step back from the silliness.
We really don’t know much about police shootings in terms of data. Very little data is publicly available – most police departments don’t keep or report data on who they shoot (race, age, etc.). So some organizations did some studies and analysis on the limited data that is out there. And they found some conflicting results.
Which, IMO, means that a lot more study is needed. And a lot more pressure ought to be put on departments to keep and report this data. And no one should be convinced by an single, or pair, of studies, with such limited data, that everything is hunky-dory and there’s absolutely no problem with police shootings.
Another important thing to consider – regardless of race, American police kill tons of people. From some back of the envelope math I did in a previous thread, American police kill over 10,000 times as many people as UK police on a per capita basis. Sure, there are more murders and more guns in America, but on a per capita basis those differences are less than a factor of 10. That can’t reasonably explain a difference in police killings of over 10,000.
So just as important (or maybe even more so) as possible racial bias in shootings is just the incredibly high rate of overall killings by police in America. It seems reasonable to suspect that maybe American police culture, practice, and policy lead to more usage of deadly force than necesary.
I can agree that more data is better than less data, that is completely separate from the question of whether we have enough data to start drawing conclusions.
And we do have enough data to start drawing conclusions. The data was sifted to make sure that we only counted jurisdictions that provided complete data. There is no reason to believe that these jurisdictions are any different than anywhere else. We may not have the entire universe of data, but we are no longer at the “we don’t really know” stage.
We KNOW that disparities as large as 3::1 can be fully explained by the differences in the circumstances of the shooting. Are 2 studies enough to put the matter to rest especially since so many people seem to doubt the conclusions? Probably not. Just like we STILL don’t have a consensus that tax cuts in the current environment don’t increase revenue. All you need is someone saying “nuh uh”