stochastic

First, there are RNGs meant for simulation of stochastic processes.

So, I got a relatively good background in stochastic processes.

But if I introduce a tiny element of stochastic displacement in your timeline, you will wonder, hey, where did this come from , when did I do that, etc.

Self experimentation might be useful, but only if you understand the metrics you measure and whether it's stochastic noise or meaningful results.

The research community has for some years been debating whether or not stochastic nuclear DNA damage is important in aging outside of the issue of cancer.

I found a much more powerful approach with some original work using some advanced topics in stochastic processes, and the lab concluded that the work was "not publishable".

However there is nowadays plenty of evidence to support the opposite view, that the levels of stochastic nuclear mutations seen in human tissues really don't matter over the present human life span.

In particular, consider working in optimization and stochastic processes with a solid background in measure theory and functional analysis.

I've studied stochastic processes, mathematical optimization, data structures and algorithms.

So, CS ran into 'information', 'knowledge', manipulating information, etc. and started borrowing ugrad texts in applied math, optimization, statistics, stochastic processes, graph theory, control theory, etc.

It's how I learned plane geometry, freshman calculus, theoretical, applied, and numerical linear algebra, everything I learned about statistics, most of what I learned about advanced calculus, signal processing and the FFT, stochastic optimal control, artificial intelligence, ..., and everything I learned about software.