The current "drug em till they don't ask tough questions and go outside the
lesson plan" treatment for the fictional ADHD money-making diagnosis is all
hogwash, lies, and downright child endagerment.(my opinion) A VERY small
minority actually has something treatable by the snake oil concotions...

Walt
On Nov 7, 2010 10:09 AM, "Peter Frederick" <psf...@earthlink.net> wrote:
> Statistics are just numbers, and the formulas used to generate them
> are NOT intelligent -- they work no matter what numbers you put in.
>
> The first lessons in a decent statistics class involve long
> discussions of this fact -- to whit, the numbers mean nothing unless
> the underlying assumptions of logical connection are true. The logic
> and measurement parameters mean everything.
>
> One should also remember that descriptive statistics are just that --
> they describe a population one has measured. Bad measuring tools
> result in bad data, at best, and descriptive statistics are NEVER
> predictive.
>
> inferential statistics (things like comparing test vs control
> subjects ) are predictive ONLY when all the assumptions made about
> measurement and logic are true (watch for a term called "external
> validity" -- it doesn't generate numbers, it's a logics problem).
> This is where statistics tend to veer off into the land of fantasy, or
> every outright lies. Just like a survey, one has to be careful about
> what data is generated to apply statistics to, and how that data
> actually applies to a problem, since if you don't measure what you
> think you are, the results are meaningless.
>
> A current example is the use of amphetamines to treat ADD or ADHD --
> all the measurements are whether the kid sits still or doesn't disrupt
> the classroom, so far as I know there are NO studies, even poor ones,
> that indicate that the kids learn more. Bogus research, so far as I'm
> concerned, and a gross misuse of statistical tools: the conclusions
> are completely un-related to the measurements. Another bad result
> here is the use of amphetamines by kids "studying" as the assume they
> lead to better learning. No evidence of that, either. The logic
> failure: compliance in the classroom is mis-labeled as "learning".
>
> Statistical process control is another thing that gets me fired up,
> since it's almost always used improperly by American management
> people. It's only useful if you use the data to control a device --
> can't be applied to employees, sales, or biological systems (with a
> few exceptions), and even then is only useful if you have a calibrated
> knob to turn. I've been told many times it's not useful for
> production since it "only finds bad parts" -- typically, the person
> telling me this missed the whole point, which is to use the
> measurement data to fix the machines MAKING the parts so that only
> good parts get made. A monkey with a go/no go gauge can find bad vs
> good parts, no need of mathematics at all, but if you want to figure
> out how to fix or replace a manufacturing tool BEFORE it makes off
> sized stuff, SPC is a miracle. Totally worthless for a pH meter,
> though -- no variation allowed in the measurements, if it's out of a
> very narrow range, you re-calibrate or repair it.
>
> I could go on and on, but the point I'd like to pass on is that one
> MUST know and understand the structure, measurements, and assumptions
> made in any study of any type using statistics before reaching any
> conclusions on the validity of the results.
>
> Peter
>
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