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Articles & Books From R
Cheat Sheet / Updated 06-16-2025
R provides a wide array of functions to help you with statistical analysis with R—from simple statistics to complex analyses. Several statistical functions are built into R and R packages. R statistical functions fall into several categories including central tendency and variability, relative standing, t-tests, analysis of variance and regression analysis.
Simplify stats and learn how to graph, analyze, and interpret data the easy way Statistical Analysis with R For Dummies makes stats approachable by combining clear explanations with practical applications. You'll learn how to download and use R and RStudio—two free, open-source tools—to learn statistics concepts, create graphs, test hypotheses, and draw meaningful conclusions.
The easy way to get started coding and analyzing data in the R programming language Statistical Analysis with R Essentials For Dummies is your reference to all the core concepts about R—the widely used, open-source programming language and data analysis tool. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff.
A deep dive into the programming language of choice for statistics and data With R All-in-One For Dummies, you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we're all swimming in. Maybe you're pursuing a career in data science, maybe you're looking to infuse a little statistics know-how into your existing career, or maybe you're just R-curious.
Cheat Sheet / Updated 01-11-2023
R provides a wide array of functions to help you with your work — from simple statistics to complex analyses.This Cheat Sheet is a handy reference for Base R statistical functions, interactive applications, machine learning, databases, and images.Base R statistical functionsHere’s a selection of statistical functions that come with the standard R installation.
Cheat Sheet / Updated 07-29-2022
R is more than just a statistical programming language. It’s also a powerful tool for all kinds of data processing and manipulation, used by a community of programmers and users, academics, and practitioners.To get the most out of R, you need to know how to access the R Help files and find help from other sources.
Cheat Sheet / Updated 05-02-2022
To complete any project using R, you work with functions that live in packages designed for specific areas. This cheat sheet provides some information about these functions.Interacting with users with R functionsHere’s a selection of statistical functions that come with the standard R installation. You’ll find many others in R packages.
Article / Updated 11-04-2021
The rbind() function in the R programming language conveniently adds the names of the vectors to the rows of the matrix. You name the values in a vector, and you can do something very similar with rows and columns in a matrix.For that, you have the functions rownames() and colnames(). Guess which one does what?
Article / Updated 10-28-2021
In the R programming language, a conversion from a matrix to a data frame can’t be used to construct a data frame with different types of values. If you combine both numeric and character data in a matrix, for example, everything will be converted to character.You can construct a data frame from scratch, though, using the data.
Article / Updated 09-30-2019
After you calculate the variance of a set of numbers, you have a value whose units are different from your original measurements. For example, if your original measurements are in inches, their variance is in square inches. This is because you square the deviations before you average them. So the variance in the five-score population in the preceding example is 6.