Damned Lies And Statistics

Years ago I worked for the Group Actuarial unit at CIGNA. Actuaries are the people that determine rates and risk. They’re big players in insurance, and becoming a full actuary instantly makes you an officer of the company at most places. Needless to say, I am not an actuary; I supported their efforts with my systems skills. I got to speaking about actuaries with an IRC chum today. If you want to know what distinguishes actuaries from statisticians in my mind, read on …

Actuaries use statistics. Actuaries need to be good statisticians. But there’s a “real world” aspect to actuarial science. It looks something like this:

ai: I wanted to be an actuary for a while.

ai: I really like statistics a lot.

strex[a] considers what he should do to be “productive” with the rest of the day

ai strex[a]: I strongly recommmend masturbation.

mneptok: and statistics.

mneptok: “4 out of 5 cumshots missed my eye”

mneptok: “7 of 10 were not blanks.”

mneptok: now

mneptok: this is where we separate statistics from actuarial work

mneptok: statistics would say that if 1 of 5 cumshots hit the eye, and 3 of 10 were blanks, that statistically eventually you would get a blank that hit you in the eye.

mneptok: actuaries know better.

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