- What is R?
- Why learning R?
- Related articles
- Infos
R is free and powerful programming language for statistical computing and data visualization.
R can be used to compute a large variety of classical statistic tests including:
- Student’s t-test comparing the means of two groups of samples
- Wilcoxon test, a non parametric alternative of t-test
- Analysis of variance (ANOVA) comparing the means of more than two groups
- Chi-square test comparing proportions/distributions
- Correlation analysis for evaluating the relationship between two or more variables
It’s also possible to use R for performing classification analysis such as:
- Principal component analysis
- clustering
Many types of graphs can be drawn using R, including: box plot, histogram, density curve, scatter plot, line plot, bar plot, …
R is open source, so it’s free.
R is cross-plateform compatible, so it can be installed on Windows, MAC OSX and Linux
R provides a wide variety of statistical techniques and graphical capabilities.
R provides the possibility to make a reproducible research by embedding script and results in a single file.
R has a vast community both in academia and in business
R is highly extensible and it has thousands of well-documented extensions (named R packages) for a very broad range of applications in the financial sector, health care,…
It’s easy to create R packages for solving particular problems
- Next chapters
- Installing R and RStudio
- Running RStudio and setting up your working directory
- R programming basics
This analysis has been performed using R software (ver. 3.2.3).
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