Read this blog to learn how to perform your first multiple linear regression in R with clear explanations and step-by-step coding examples. This tutorial simplifies statistical modeling, helping you ...

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 ...

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...

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 ...

Although there are many measures of variability for qualitative variables, they are little used in social research, nor are they included in statistical software. The aim of this article is to present ...

This tutorial illustrates how to read spatial data (i.e., a raster) from a netCDF file and import it into R for plotting and analysis. # Install and Load Packages In addition to the built-in ...

Pathological cardiac hypertrophy is the main predecessor of heart failure. Its pathology is sophisticated, and its progression is associated with multiple cellular processes. To explore new ...

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) ...