Continuing our series — see here for Part 1, and Part 2 — let’s look at Makin and Orban de Xivry’s Statistical Mistake #4: Spurious Correlations. This one is easy to understand, though nonetheless common. The authors refer to situations like the one illustrated in their Figure 2, shown below, in which the correlation calculated … Continue reading Comments on “Ten common statistical mistakes…”: #4
Continuing from the first post in this series, let’s look at Makin and Orban de Xivry’s Statistical Mistake #3: Inflating the units of analysis. The issue: What is N? In other words, how many independent data points are there, for whatever statistical analysis one wants to do? N is often mistakenly made larger than it … Continue reading Comments on “Ten common statistical mistakes…”: #3
The steady stream of scientific articles with irreproducible results, shaky conclusions, and poor reasoning  is, thankfully, accompanied by attempts to do something about it. A few months ago, Tamar Makin and Jean-Jacques Orban de Xivry published an excellent short article called “Ten common statistical mistakes to watch out for when writing or reviewing a … Continue reading Comments on “Ten common statistical mistakes…”: #1 and #2
[Note: a long post of interest only to people who care about data analysis and bad statistics, and maybe about the distant stars influencing your life.] By now, we should all be able to list the many reasons that p-values (or null-hypothesis-significance-testing, NHST) are awful: that “statistical significance” has nothing to do with effect size … Continue reading How do I hate p-values? Let me count the ways…
There’s been an flurry of papers and essays in the past few years on scientific studies being wrong, arguing that the number of incorrect conclusions is disturbingly large, and symptomatic of poor practice, misplaced incentives, and other factors. Perhaps the most widely seen views on this theme graced the cover of The Economist a … Continue reading If I keep writing, maybe this post will become significant
At a café not long ago, I overheard some students sitting by me complaining that their error analysis exercise for a physics lab class was extremely boring (involving e.g. propagation of errors in measurements). Usually, when I hear griping about classes I have to restrain myself from throwing coffee cups, but in this case I … Continue reading Statistics!