# Re: Is Racial Profiling a Type of Bayesian Inference?

*From*: Russell <russell.martin@xxxxxxx>*Date*: Sat, 25 Jul 2009 17:49:03 -0700 (PDT)

On Jul 25, 8:43 pm, aruzinsky <aruzin...@xxxxxxxxxxxxxxxxxxxx> wrote:

On Jul 25, 10:40 am, Russell <russell.mar...@xxxxxxx> wrote:

On Jul 25, 11:34 am, aruzinsky <aruzin...@xxxxxxxxxxxxxxxxxxxx> wrote:

On Jul 24, 6:12 pm, Russell <russell.mar...@xxxxxxx> wrote:

On Jul 24, 6:51 pm, aruzinsky <aruzin...@xxxxxxxxxxxxxxxxxxxx> wrote:

On Jul 24, 10:44 am, Russell <russell.mar...@xxxxxxx> wrote:

On Jul 23, 8:41 pm, aruzinsky <aruzin...@xxxxxxxxxxxxxxxxxxxx> wrote:

I'm certain that racial profiling is an informal application of

statistics, but I am uncertain of the kind of statistics.

I shouldn't touch this topic with a 10 foot pole, but...

It's a Yes or No question!

Please note that the body of your post, which was what I

addressed, was "I'm certain that racial profiling is an

informal application of statistics, but I am uncertain

of the kind of statistics.", which in fact is not a

question at all.

My motto is all too often the study of data requires cares.

A corollary of that might be there is no such thing as

informal statistics. Either the methodology is applied

carefully or it isn't really statistics, just quackery.

A euphemism for "fudge" is "model" as in "Gaussian white noise

model." Name one area of applied statistics without fudge.

A famous statistician once said, "All models are wrong. Some

are useful."

I'm sure many officers try hard, I doubt if the people in

law enforcement, especially on patrol, have the time for

careful analysis, even if they have the desire and skills.

I'm more inclined to believe that cognitive illusions tend

to take over, driven by the heuristics hardwired into our

brains by millions of years of evolution (see the book

_Inevitable Illusions: How Mistakes of Reason Rule Our

Minds_, or several others that deal with these ideas).

Good training helps condition officers to control their

reactions to these hueristics, and in some cases the

hueristics may even invoke the correct response and

should be followed.

But in any case, it's not statistics,

at least as I use the word. Just my opinion...

Cheers,

Russell

I am leaning toward informal statistical decision theory. You do not

have to know the exact number of bullet chambers in a gun to quickly

decide not to play Russian roulette.

That's a classic a risk analysis.

Cheers,

Russell- Hide quoted text -

- Show quoted text -

My point was that racial profiling typically attempts to optimize

costs (maximizing expected utility) whereas Bayesian Inference does

not therefore calling it an application of statistical decision theory

is more appropriate.

See

http://www.infra.kth.se/~soh/decisiontheory.pdf

As statistical decision theory, racial profiling can be done more

rigorously to set police policy.

It is possible to get crime statistics, e.g., here

http://www.informaworld.com/smpp/1820777723-94262195/content~db=all~c...

and guesstimate the utility costs. An advantage of this procedure is

that points of contention (probably utility costs) can easily be

recognized compared to recognizing points of contention in endless

hours of tradition debate using connotative words and denotatively

ambiguous homonyms such as "racist."- Hide quoted text -

- Show quoted text -

My point is that the results don't have to be perfect,

the assumptions of the models will never be perfectly

met in real life data (if they were, I'd think the data

suspect), but these things need to be done with care

and interpreted with care to be truly useful. One can

download all the data one can find, but how good is the

data? What else are potential sources of statistical

bias in the data? What covariates are highly colinear

with race and crime? Correlation is not causation.

Such things need to be studied before one even decides

whether to use technique A or B for the analysis. (You

might be right in your choice of technique. I don't

know.) One will almost certainly find the data wanting

in some respect. What might that do to the results?

I agree that endless hours of debate might be illuminated

by actual facts. But I don't want armed police making

decisions based on a guesstimate of the utility costs or

guesstimates produced in whatever statistical framework

one thinks is most applicable. It's not that such

results are necessarily fundamentally wrong in all

cases, but they might be wrong in too many cases and they

might provide a cloak of scientific respectability for

decisions that is not justified.

Cheers,

Russell- Hide quoted text -

- Show quoted text -

But, you are already a voluntary user of grossly inaccurate

guesstimation. You are making an important decision based on "might",

i.e., nonzero probability, instead of more accurate probability

estimates

The use of the word "might" in this case is rhetorical

rather than statistical, and even if it wasn't, I'm not

going to draw a gun based on the resulting probabilities.

Cheers,

Russell

.

**Follow-Ups**:**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*aruzinsky

**References**:**Is Racial Profiling a Type of Bayesian Inference?***From:*aruzinsky

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*Russell

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*aruzinsky

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*Russell

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*aruzinsky

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*Russell

**Re: Is Racial Profiling a Type of Bayesian Inference?***From:*aruzinsky

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