If you compute the standard deviation of a data set by directly implementing the definition, you’ll need to pass through the data twice: once to find the mean, then a second time to accumulate the squared differences from the mean.…Read more ›
If you compute the standard deviation of a data set by directly implementing the definition, you’ll need to pass through the data twice: once to find the mean, then a second time to accumulate the squared differences from the mean.…Read more ›
One problem with the nothing-to-hide argument is that it assumes innocent people will be exonerated certainly and effortlessly. That is, it assumes that there are no errors, or if there are, they are resolved quickly and easily. Suppose the probability…Read more ›
Matt Brigg’s comment on outliers in his post Tyranny of the mean: Coontz used the word “outliers”. There are no such things. There can be mismeasured data, i.e. incorrect data, say when you tried to measure air temperature but your…Read more ›
Sometimes you can approximate a binomial distribution with a normal distribution. Under the right conditions, a Binomial(n, p) has approximately the distribution of a normal with the same mean and variance, i.e. mean np and variance np(1-p). The approximation works…Read more ›
I needed to compute the higher moments of a mixture distribution for a project I’m working on. I’m writing up the code here in case anyone else finds this useful. (And in case I’ll find it useful in the future.)…Read more ›
I hear a lot of people saying that simple models work better than complex models when you have enough data. For example, here’s a tweet from Giuseppe Paleologo this morning: Isn’t it ironic that almost all known results in asymptotic…Read more ›
In Thinking, Fast and Slow, Daniel Kahneman comments on The robust beauty of improper linear models in decision making by Robyn Dawes. According to Dawes, or at least Kahneman’s summary of Dawes, simply averaging a few relevant predictors may work…Read more ›
It’s a simple rule of probability that if A makes B more likely, B makes A more likely. That is, if the conditional probability of A given B is larger than the probability of A alone, the the conditional probability…Read more ›
This afternoon Hadley Wickham gave a great talk on data analysis. Here’s a paraphrase of something profound he said. Visualization can surprise you, but it doesn’t scale well. Modelling scales well, but it can’t surprise you. Visualization can show you…Read more ›
Andrew Gelman is trying to collect 365 stories about life as a statistician: So here’s the plan. 365 of you write vignettes about your statistical lives. Get into the nitty gritty—tell me what you do, and why you’re doing it.…Read more ›
