Most of my friends with families fret over school quality when deciding where to buy their homes. It's well known that good school districts are also associated with expensive houses. A feedback cycle is at work here: home prices surge where there are good schools; only richer people can afford to buy such homes; wealth brings other advantages, and so the schools tend to have better students, which leads to…
You probably already saw the video - if not, do yourself a favor, and search for "man forcibly removed from overbooked United flight." Other than the video evidence, which is damning, we don't have many facts, other than assertions made by various parties, repeated endlessly on social media and mainline media. Some facts, such as the United CEO claiming the passenger was "belligerent," is an assault on the meaning of…
sigr is a simple R package that conveniently formats a few statistics and their significance tests. This allows the analyst to use the correct test no matter what modeling package or procedure they use. Model Example Let’s take as our example the following linear relation between x and y: library('sigr') set.seed(353525) d <- data.frame(x= rnorm(5)) … Continue reading sigr: Simple Significance Reporting
One thing I teach is: when evaluating the performance of regression models you should not use correlation as your score. This is because correlation tells you if a re-scaling of your result is useful, but you want to know if the result in your hand is in fact useful. For example: the Mars Climate Orbiter … Continue reading Be careful evaluating model predictions
If you live in the States, and particularly a blue state, in the last year or two, it has been drilled into your head that Hillary Clinton was the overwhelming favorite to win the Presidential election. On the day before the election, when all the major media outlets finalized their "election forecasting models," they unanimously pronounced Clinton the clear winner, with a probability of winning of 70% to 99%. One…
This is the third and final post about the controversy over statistical analysis used in peer-reviewed published scholarly research. Most of the new stuff are covered in post #2 (link). Today's post covers statistical issues related to sample size, which is nothing new, but it was mentioned in Amy Cuddy's response to her critics and thus I also discuss it here. In post #2 (link), I offer the following mental…
Yesterday, I started a series of posts covering the "power pose" research controversy. The plan is as follows: Key Idea 1: Peer Review, Manuscripts, Pop Science and TED Talks Key Idea 2: P < 0.05, P-hacking, Replication Studies, Pre-registration Key Idea 3: Negative Studies, and the File Drawer (Today) Key Idea 4: Degrees of Freedom, and the Garden of Forking Paths Key Idea 5: Sample Size Here is a quick…
I recently covered the power pose research controversy, ignited by an inflammatory letter by Susan Fiske (link). Dana Carney, one of the coauthors of the original power pose study, courageously came forward to disown the research, and explained the reasons why she no longer trusts the result. Here is her mea culpa. Her co-author, Amy Cuddy, then went to New York Magazine to publish her own corrective, claiming that the…
One of my favorite statistics-related wisecracks is: the plural of anecdote is not data. In today's world, the saying should really say: the plural of anecdote is not BIG DATA. In class this week, we discussed a recent Letter to the Editor of top journal, New England Journal of Medicine, featuring a short analysis of weight data coming from a digital scale that, you guessed it, makes users consent to…
One of my favorite statistics-related wisecracks is: the plural of anecdote is not data. In today's world, the saying should really say: the plural of anecdote is not BIG DATA. In class this week, we discussed a recent Letter to the Editor of top journal, New England Journal of Medicine, featuring a short analysis of weight data coming from a digital scale that, you guessed it, makes users consent to…
