As a scientist, watching the Brexit vote was a little bit painful. Though probably not for the reason you're thinking. No, it wasn't the politics that bothered me, but the method for making such an incredibly important decision. Let me explain...
Scientists are a bit obsessed with the concept of error. In the context of collecting data and anaylzing it, this takes the form of our "confidence" in the results. If all the data say the same thing, then we are usually pretty confident in the overall message. If the data is more complicated than this (and it always is), then we need to define how confident
When we discuss "computational efficiency", you often hear people throw around phrases like $O(n^2)$ or $O(nlogn)$. We talk about them in the abstract, and it can be hard to appreciate what these distinctions mean and how important they are. So let's take a quick look at what computational efficiency looks like in the context of a very famous algorithm: The Fourier Transform.
NIH Fellowship Success Rates¶
As I'm entering the final years of graduate school, I've been applying for a few typical "pre-doc" fellowships. One of these is the NRSA, which is notorious for requiring you to wade through forests of beaurocratic documents (seriously, their "guidelines" for writing an NRSA are over 100 pages!). Doing so ends up taking a LOT of time.
Using Craigslist to compare prices in the Bay Area¶
In the last post I showed how to use a simple python bot to scrape data from Criagslist. This is a quick follow-up to take a peek at the data.
Note - data that you scrape from Craigslist is pretty limited. They tend to clear out old posts, and you can only scrape from recent posts anyway to avoid them blocking you.