Attribution Based on Tail Probabilities
ModelingStatisticsposted by John Cook July 25, 2018
If all you know about a person is that he or she is around 5′ 7″, it’s a toss-up whether this person is male or female. If you know someone is over 6′ tall, they’re probably male. If you hear they are over 7″ tall, they’re... Read more
ECDFs: “Empirical Cumulative Distribution Function”
ModelingStatisticsposted by Eric Ma July 23, 2018
In my two SciPy 2018 co-taught tutorials, I made the case that ECDFs provide richer information compared to histograms. My main points were: We can more easily identify central tendency measures, in particular, the median, compared to a histogram. We can much more easily identify other... Read more
How Far is xy From yx on Average for Quaternions?
ModelingStatisticsposted by John Cook July 16, 2018
Given two quaternions x and y, the product xy might equal the product yx, but in general the two results are different. How different are xy and yx on average? That is, if you selected quaternions x and y at random, how big would you expect the difference xy – yx to be? Since this difference would increase proportionately if you increased the length... Read more
Low-Rank Matrix Perturbations
ModelingStatisticsposted by John Cook July 12, 2018
Here are a couple of linear algebra identities that can be very useful, but aren’t that widely known, somewhere between common knowledge and arcane. Neither result assumes any matrix has low rank, but their most common application, at least in my experience, is in the context... Read more
Linear Regression and Planet Spacing
ModelingStatisticsposted by John Cook July 6, 2018
Linear Regression and Planet Spacing A while back I wrote about how planets are evenly spaced on a log scale. I made a bunch of plots, based on our solar system and the extrasolar systems with the most planets, and said noted that they’re all roughly straight... Read more
Statistical Software Matters
ModelingStatisticsposted by Thomas Lumley June 29, 2018
This is a picture of all the genetic associations found in genome-wide association studies, sorted by chromosome. You can find more detail at the NHGRI GWAS catalog There are two chromosomes with many fewer associations. One is the Y chromosome. There isn’t much there because... Read more
Partition numbers and Ramanujan’s approximation
ModelingStatisticsposted by John Cook June 25, 2018
The partition function p(n) counts the number of ways n unlabeled things can be partitioned into non-empty sets. (Contrast with Bell numbers that count partitions of labeled things.) There’s no simple expression for p(n), but Ramanujan discovered a fairly simple asymptotic approximation: How accurate is this approximation? Here’s a little Matheamtica code to see.... Read more
Talking About Clinical Significance
ModelingStatisticsposted by John Mount June 22, 2018
In statistical work in the age of big data we often get hung up on differences that are statistically significant (reliable enough to show up again and again in repeated measurements), but clinically insignificant (visible in aggregation, but too small to make any real difference to individuals). An example would... Read more
Stirling Numbers, Including Negative Arguments
ModelingStatisticsposted by John Cook June 20, 2018
Stirling numbers are something like binomial coefficients. They come in two varieties, imaginatively called the first kind and second kind. Unfortunately it is the second kind that are simpler to describe and that come up more often in applications, so we’ll start there. Stirling numbers of... Read more
Fixed Points of Logistic Function
ModelingStatisticsposted by John Cook June 15, 2018
Here’s an interesting problem that came out of a logistic regression application. The input variable was between 0 and 1, and someone asked when and where the logistic transformation f(x) = 1/(1 + exp(a + bx)) has a fixed point, i.e. f(x) = x. So given logistic regression parameters a and b, when does... Read more