E(f(X))

Whenever I get home, I look for the blinking light on the answering machine. That means messages, perhaps from employers! Unfortunately, today's message was a hang-up, so back to applying for jobs again.

In Dr. N's class, we did negative binomial problems. At the beginning of class, Dr. N asked me, "so have you been to another university?" Yep, I have a degree in math from 1987. Looks like he found the ringer in his classroom.

Dr. Z didn't return the Intro Stats test, but he covered some new material -- thank goodness, I was tired of listening to him go over elementary probability for the last month. The infamous "Student T" distribution was introduced. Why you would choose this distribution for samples where n < 30 isn't made clear, but at least it's new interesting material.

Dr. S talked about Moment Generating Functions. Yes, every actuary knows what they are, but as it turns out E(X^3), E(X^4) and all those other higher moments have a use. As it turns out, from Taylor's Theorem, any function has a polynomial expansion (plus remainer) for a certain interval about x, so you could estimate E(f(X)) by finding E(a-sub-n * X^N + a-sub-(n-1) * X^(N-1) + a-sub-1 * X + a-sub 0 + R(X)), and pray that R(X) doesn't blow up.

Other than that, time to rest, do some problems, prepare for the Intro Probability test next Wednesday.

I also notice that the blog gets a lot of hits regarding Exam P. If I knew what information people were looking for, I'd point them to it.