What statistics concepts are useful for profiling?
math, optimization, profiling, statistics
Solution
I'm not sure books on statistics are that useful when it comes to profiling. Running a profiler should give you a list of functions and the percentage of time spent in each. You then look at the one that took the most percentage wise and see if you can optimise it in any way. Repeat until your code is fast enough. Not much scope for standard deviation or chi squared there, I feel.
Problem
I've been meaning to do a little bit of brushing up on my knowledge of statistics. One area where it seems like statistics would be helpful is in profiling code. I say this because it seems like profiling almost always involves me trying to pull some information from a large amount of data. Are there any subjects in statistics that I could brush up on to get a better understanding of profiler output? Bonus points if you can point me to a book or other resource that will help me understand these subjects better.