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“Statistics to English Translation”

The core of our “statistics to English translation” series is Nina Zumel’s sequence of articles: “I don’t think that means what you think it means;” Statistics to English Translation, Part 1: Accuracy Measures Statistics to English Translation, Part 2a: ’Significant’ Doesn’t Always Mean ’Important’ Statistics to English Translation, Part 2b: […]

On The Decomposition of Variance

I am conducting another machine learning / AI bootcamp this week. Starting one of these always makes me want to get more statistical commentaries down, just in case I need one. These classes have to move fast, and also move correctly. In this case I want to write about decomposition […]

A Gruesome Example of Bayes’ Law

Here is an incredibly clear, but unfortunately gruesome, example of a variation of Bayes’ Law. A good teachable point. Consider the recent CDC article “Community and Close Contact Exposures Associated with COVID-19 Among Symptomatic Adults ≥18 Years in 11 Outpatient Health Care Facilities.” It states: Adults with positive SARS-CoV-2 test […]

The Intercept Fallacy

A common mis-understanding of linear regression and logistic regression is that the intercept is thought to encode the unconditional mean or the training data prevalence. This is easily seen to not be the case. Consider the following example in R. library(wrapr) We set up our example data. # build our […]

New WVPlot: ROCPlotPairList

We have a new R WVPlots plot: ROCPlotPairList. It is useful for comparing the ROC/AUC of multiple models on the same data set. library(WVPlots) set.seed(34903490) x1 <- rnorm(50) x2 <- rnorm(length(x1)) x3 <- rnorm(length(x1)) y <- 0.2*x2^2 + 0.5*x2 + x1 + rnorm(length(x1)) frm <- data.frame( x1 = x1, x2 […]

Why not Square Error for Classification?

Win Vector LLC has been developing and delivering a lot of “statistics, machine learning, and data science for engineers” intensives in the past few years. These are bootcamps, or workshops, designed to help software engineers become more comfortable with machine learning and artificial intelligence tools. The current thinking is: not […]

Unrolling the ROC

In our data science teaching, we present the ROC plot (and the area under the curve of the plot, or AUC) as a useful tool for evaluating score-based classifier models, as well as for comparing multiple such models. The ROC is informative and useful, but it’s also perhaps overly concise […]