Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

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 ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

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 ...

The R programming language is an important tool for development in the numeric analysis and machine learning spaces. With machines becoming more important as data generators, the popularity of the ...

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 ...

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in ...