R is a programming language and free software environment for statistics. R is a language built for a specific purpose. It is strictly designed for statistical analysis. The algorithms for many statistical models are devised in R. Precisely R is the language of Statistical Analyzers. It’s an open source and the best suite for the statisticians to develop statistical softwares. R is putting utmost efforts to walk parallelly to Python.
Usage in other areas
The R language was originally made for statistics. But today, it is also used in many scientific fields including ecology.
Development history
A list of changes in R releases is maintained in various "news" files at CRAN (Comprehensive R Archive Network). Some highlights are listed below for several major releases.
Communities
R has local communities worldwide for users to share ideas and learn.
There are a growing number of R events bringing its users together, such as conferences (e.g. useR!, WhyR?, conectaR, SatRdays) and other meetups.
useR! conferences
The official annual gathering of R users is called "useR!". The first such event was useR! 2004 in May 2004, Vienna, Austria. After skipping 2005, the useR! conference has been held annually. Subsequent conferences have included: useR! 2006, Vienna, Austria useR! 2007, Ames, Iowa, USA useR! 2008, Dortmund, Germany useR! 2009, Rennes, France useR! 2010, Gaithersburg, Maryland, USA useR! 2011, Coventry, United Kingdom useR! 2012, Nashville, Tennessee, USA useR! 2013, Albacete, Spain useR! 2014, Los Angeles, California, USA useR! 2015, Aalborg, Denmark useR! 2016, Stanford, California, USA useR! 2017, Brussels, Belgium useR! 2018, Brisbane, Australia useR! 2019, Toulouse, France
Future conferences planned are as follows: useR! 2020, St. Louis, Missouri, USA (Canceled) useR! 2021, Zurich, Switzerland
The R Journal
The R Journal is the open access refereed journal of the R project. It features articles on the use and development of the R language.
Basic syntax
The following examples illustrate the basic syntax of the language and use of the command-line interface.
In R, the generally preferred assignment operator is an arrow made from two characters <-. Although = can be used instead. > x <- 1:6 # Create vector. > y <- x^2 # Create vector by formula. > print(y) # Print the vector’s contents. [1] 1 4 9 16 25 36
> mean(y) # Arithmetic mean of vector. [1] 15.16667
> var(y) # Sample variance of vector. [1] 178.9667
> model <- lm(y ~ x) # Linear regression model y = A + B * x. > print(model) # Print the model’s results.
Call: lm(formula = y ~ x)
Coefficients: (Intercept) x -9.333 7.000
> summary(model) # Display an in-depth summary of the model.
Call: lm(formula = y ~ x)
Residuals: 1 2 3 4 5 6 3.3333 -0.6667 -2.6667 -2.6667 -0.6667 3.3333
Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -9.3333 2.8441 -3.282 0.030453 * x 7.0000 0.7303 9.585 0.000662 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.055 on 4 degrees of freedom
Multiple R-squared: 0.9583, Adjusted R-squared: 0.9478
F-statistic: 91.88 on 1 and 4 DF, p-value: 0.000662
> par(mfrow = c(2, 2)) # Create a 2 by 2 layout for figures. > plot(model) # Output diagnostic plots of the model.