Author: John Mount
This note is just a quick follow-up to our last note on correcting the bias in estimated standard deviations for binomial experiments. For normal deviates there is, of course, a...continue reading.
One of the concepts we teach in both Practical Data Science with R and in our theory of data shaping is the importance of identifying the roles of columns in...continue reading.
R is an interpreted programming language with vectorized data structures. This means a single R command can ask for very many arithmetic operations to be performed. This also means R...continue reading.
Authors: John Mount, and Nina Zumel 2018-10-25 As a followup to our previous post, this post goes a bit deeper into reasoning about data transforms using the cdata package. The...continue reading.
Introduction Let’s take a quick look at a very important and common experimental problem: checking if the difference in success rates of two Binomial experiments is statistically significant. This can...continue reading.
Our interference from then environment issue was a bit subtle. But there are variations that can be a bit more insidious. Please consider the following. library(“dplyr”) # unrelated value that...continue reading.