Data analysis software makes sense of large amounts of information quickly. Tools like R, Python, and SPSS simplify research and statistical studies. Visualization platforms like Tableau and Power BI ...

The discovr package contains resources for my 2026 textbook Discovering Statistics Using and . There are tutorials written using learnr. Once a tutorial is running it’s a bit like reading a book but ...

The identification and visualization of functional elements within biological sequences offers visual presentation for biologists to integrate annotation, and also helps them to produce high-quality ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

For everything from styling text and customizing color palettes to creating your own geoms, these ggplot2 add-ons deserve a place in your R data visualization toolkit. Plus, a bonus list of packages ...

The analysis of spatial point patterns has greatly advanced our understanding of ecological processes. However, the methods currently available for analyzing replicated spatial point patterns (RSPPs) ...

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 ...

R is an open source programming language especially designed for manipulating data and performing statistical analysis. It is very similar to SAS Enterprise Guide except: R is a programming language.

1 Department of Electronics, Computing and Mathematics, University of Derby, Derby, UK. 2 Department of Computer Science and Intelligent Systems, Iwate University, Morioka, Japan. 3 BAC International ...