[tansey]

When I first graduated from college, I took an R&D position doing financial modeling. Multiple times a day, I would walk into my boss's office to tell him I had no idea how to implement the next part. He would start to explain and then use a term like "Gaussian distribution" and I'd have to stop him. Down the rabbit hole we went, filling up the white board with graphs and formula. Once we reached the point where I was adept enough to proceed ("oh, ok, so you just add them all.") we would begin to pop things back off the stack until we were back at the original problem.

It was a painful process for me. I'm sure it was even more painful for my boss. After a couple of months, I reached a point where I didn't really need help deciphering statistics.

A few months later, I read through the code of a co-worker who had been there much longer. I noticed some deficiencies in a statistical search method. When I asked my boss why my co-worker implemented all his models using such a poor technique, he told me, "Because he doesn't come into my office and say he has no idea what he's doing."

[reeses]

As a manager, this is the best part of my job. Almost every other bit is drudgery, administration, and distasteful politics.[1]

I love it when an engineer, junior or senior, wanders over and asks a question about something deep or complicated. We can write math or pseudocode on the whiteboard. Even just drawing ``network'' diagrams of things talking to other things helps get me through the day.[2] It's especially rewarding when the lightbulb goes on.

I'm willing to be late to meetings with executives, skip lunch, or stay late at night for these sessions. Don't assume your boss found it painful at all. It's quite likely the best part of his day.

I had the advantage of the same sort of boss at my first real job. In retrospect, he was remarkably patient with me, showing me how to _learn_ the craft of developing software. I had previously been a hack, and he gave me enough knowledge to build my own skillset extremely quickly. (Secret weapons are always handy.)

[1] I went into management because I have an authority problem. Principally, a problem when I perceive ill-informed or untalented authority figures making poor choices that affect me. After a year or two in management, when I learned enough about operations, finance, marketing, etc., I came to the realization that I'm now just in the middle of a pyramid of the same problem. However, I stay because I have priced myself out of the programmer market. I now use the extra money to bootstrap a startup with a friend and save the rest away from the "emergency/retirement" fund so I can burn longer when I do jump ship.

[2] I am not unaware that this is vain and probably more of a status issue than altruism. ``I've still got it,'' and all that.

[Confusion]

People get hired into an R&D position doing financial modeling when they've never heard of a Gaussian distribution?

[tansey]

It wasn't quite that simple. Yes I'd heard of it, but I didn't know how to randomly sample from a Gaussian distribution, nor why it was necessary to use it in the algorithm I was working on ("why can't I just sample from a uniform distribution?").[1]

Also, I was in a special situation. I had a strong passion for the work I was doing, knew my boss before I got hired, and had done related research that showed I was able to push my way through challenging problems.

[1] http://www.nashcoding.com/2010/07/07/evolutionary-algorithms...

[NY_USA_Hacker]

Sample from a univariate distribution by taking the inverse function of the cumulative distribution and plugging in a [0,1] uniform random number. So, if X is a real valued random variable, then its 'cumulative distribution' F_X(x) = P(X <= x) where P denotes probability. Then F_X is monotone increasing so has an inverse function, say, G(u) = F_X^(-1). Then if U is a random variable uniform on [0,1], G(U) has distribution F_X like X does. Note: Have to patch up a little in the case F_X is not strictly monotone increasing.

For the inverse of the mean zero, variance 1 Gaussian distribution, look in the old NBS AMS-55 math handbook. They have two nice, simple formulas that are plenty good as approximations; one formula is a little more accurate than the other.

For getting samles from a multivariate Gaussian, that is the second lecture!

[OncomingStorm]

That's fucking awesome!