Vectors, lists, arrays, matrices and data frames -- a look at five of the most fundamental data structures built into R. Among my colleagues, R is one of the fastest-growing programming languages.

In today's data-driven world, statistical analysis plays a critical role in uncovering insights, validating hypotheses, and driving decision-making across industries. R, a powerful programming ...

A few years ago I was the CTO and co-founder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can ...

Let's use this classical statistics technique -- and some R, of course -- to get to some of the latent variables hiding in your data. Factor analysis is a classical statistics technique that examines ...

Posit’s ggbot2 is a voice assistant for ggplot2. Tell it what you want in a spoken conversation, and it will generate plots and ggplot2 R code from your data. Typing questions into a chatbot is nice, ...

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of ...

In studies on HSCT Kaplan–Meier (KM) estimates of survival curves and Cox proportional hazard models are widely used to describe survival trends and identify significant prognostic factors. All these ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...

Before you start analyzing, you might want to take a look at your data object’s structure and a few row entries. If it’s a 2-dimensional table of data stored in an R data frame object with rows and ...