Re: IQ and Testosterone?

Larry Caldwell (larryc@teleport.com)
Wed, 04 Sep 1996 04:54:47 -0700

In article <322B7F01.F70@megafauna.com>,
Stephen Barnard <steve@megafauna.com> wrote:

> Statistics show that male teenagers are far more likely to have automobile
> accidents than, for example, women over the age of forty. Therefore insurance
> companies charge *much* more to insure a male teenager than they charge to
> insure his mother. They are making a perfectly understandable judgement that
> the teenager is more likely to be an unsafe driver than is his mother. This is
> what actuarial science is all about. It extends to every kind of insurance --
> life, medical, accident, whatever. The result is that actions are taken with
> respect to individuals based on statistical information.

You did just fine until your last sentence. Actions are taken with respect
to a *population* based on statistical information. Insurance companies are
quite aware that individual variation exists. That's why they base rates
on driving record, and require medical exams before writing life insurance.
If you have cystic fibrosis, nobody is going to write your life insurance
policy no matter what your stats say.

Another example is group medical insurance. There is a minimum group size
at which point the risk becomes unacceptably large. Actuaries understand
this very well.

> There are many other arenas in which more or less the same thing goes on --
> compiling mailing lists for political contributions, targeted mass mailing,
> focus groups, etc.

To be sure, statistics can be useful. They just don't apply to individuals.

If you have studied statistics you have doubtless encountered methods of
calculating sample variance. The existance of these formulas leads many
people to assume that they are valid in all circumstances. In fact,
statistics textbooks are careful to point out that sample distribution
is only predictable if your sampling technique is invariant. No matter
how much data you have about a population, it does not extend to an
unsampled individual outside that population. You don't even know if
their response will fall within the previously tested range.

-- Larry