I recently came across this fun probability problem which I’ve dubbed the ‘Sum Over 1’ problem. It goes like this:
On average, how many random draws from the interval [0, 1] are necessary to ensure that their sum exceeds 1?
To answer this question we’ll use some probability theory (probability rules, distribution functions, expected value) and a dash of calculus (integration).
As part of the NCSU Statistical Learning Group (SLG), I gave a 50-minute overview of supervised classification methods in the machine learning literature. My presentation was aimed at an audience of primarily undergraduate and graduate students, not all of whom were statisticians. Please enjoy the videos below and follow along with slides (html) and code (Rmd) in the accompanying GitHub repository. The slides were produced using
RMarkdown v2.0 and
I introduce the motivation and goals of the NCSU Statistical Learning Group (SLG).