A few years ago, I was the CTO and cofounder 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 ...

Before you can analyze and visualize data, you have to get that data into R. There are various ways to do this, depending on how your data is formatted and where it’s located. Usually, the function ...

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 ...

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 ...

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 ...

This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...

Simply put by one of its staunchest advocates, "R is the most powerful statistical computing language on the planet; there is no statistical equation that cannot be calculated in R." Beyond "just" a ...

Do you have some data with geolocation information that you want to map? You may not think of R when you’re looking for a GIS platform, but new packages and standards have helped make the R ...