Below is an exploration of heavy tails using Python, and some of the problems they present for analysis. Heavy tails are distributions with extremely “fat tails”, they have very high likelihood of extreme values relative to a normal bell curve or even a log normal distribution.
In the previous exercise: Why do we need N-2?, I show a simple 1 dimensional regression by hand, which is followed by an examination of sample standard errors. Below I make more extensive use of R (and an additional package) to plot what linear regression looks like in multiple dimensions. This generates the images above, […]
As a department, we had a meeting about jobs in economics. I collected some information on the subject. Out of 31656 job postings, most summaries are duplicates- the positions may be different, but the first 30 words of the summary were the same. Here are the results of 638 unique postings for “economics entry level” […]
While this is hardly a tutorial, I’ve been spending a good deal of time working with zero-inflated data for a forthcoming project, and have worked with it extensively in the past. The point of zero-inflated models is there are ultimately two sources of zeros, zeros can come from the primary model (usually Poisson), or they […]
A simple chart in one place. This figure was a nice-looking variant to a paper that was ultimately accepted in EEJ. This figure itself didn’t make it, but it is a really good-looking one. This is a heat map of all accidents in NYC, from July 2012 through March 2019. Black areas are few accidents, […]