- From 2020:, the different ways the term “weights” is used in statistics and when it matters. See also, when is and isn’t it ok to just subset a survey data set by dropping records
- From 2019: What have I got against the Shapiro-Wilk test?
- From May: Why causal models are relevant to prediction: because they are relevant to generalisation. See also, mushrooms as an example
- From February: Co-linearity. “Collinearity diagnostics aren’t much help, because they don’t tell you whether you’re interested in βX or γX. What they tell you is that if you’re interested in γX it sucks to be you, because the data don’t provide much information about γX”
- The April 1 post. You can do matrix multiplication with joins. This is not completely a joke
- From August: Pictures of code are not code.
And one that didn’t get popular but that I liked: Data is the new oil