Posts discussing statistical analysis (not necessarily specific to R)

Missing Values, Data Science and R

by Joseph Rickert One great advantages of working in R is the quantity and sophistication of the statistical functions and techniques available. For example, R’s quantile() function allows you to select one of the nine different methods for computing quantiles. Who would have thought there could be so many ways to do something that seems [...]

Naive Bayes: A Generative Model and Big Data Classifier

by Joseph Rickert I found my way into data science and machine learning relatively late in my career. When I began reading papers on supervised learning I was delighted to find that good old logistic regression was considered a “go to” classifier. This was like learning that an old friend was admired for an achievement [...]

Book Review: Computer Age Statistical Inference

by Joseph Rickert Computer Age Statistical Inference: Algorithms, Evidence and Data Science by Bradley Efron and Trevor Hastie is a brilliant read. If you are only ever going to buy one statistics book, or if you are thinking of updating your library and retiring a dozen or so dusty stats texts, this book would be [...]

Creating Interactive Plots with R and Highcharts

By Mine Cetinkaya-Rundel Sometimes great ideas come from trying to solve simple problems. This seems to be especially true for software developers who are willing to put in an unreasonable amount of effort to solve a simple problem to their satisfaction. So the story goes that Torstein Hønsi, the founder and Chief Product Officer of [...]

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