Title: R (programming language) Content: R is a programming language and free software environment for statistics.Crawley, M. J. (2012). The R book. John Wiley & Sons.Dalgaard, P. (2008). Introductory statistics with R. Springer.Maronna, R. A., Martin, R. D., & Yohai, V. J. (2019). Robust statistics: theory and methods (with R). John Wiley & Sons.Ugarte, M. D., Militino, A. F., & Arnholt, A. T. (2008). Probability and Statistics with R. CRC Press.Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. O'Reilly Media.Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press. 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 ==Usage in other areas== The R language was originally made for statistics.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.Borcard, D., Gillet, F., & Legendre, P. (2018). Numerical ecology with R. Springer.Bolker, B. M. (2008). Ecological models and data in R. Princeton University Press. == Development history == A list of changes in R releases is maintained in various "news" files at CRAN (Comprehensive R Archive Network).Changes in versions 3.0.0 onward: Earlier change logs (by major release number): * * * * * 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. Diagnostic plots from plotting “model” (q.v. “plot.lm” function). Notice the mathematical notation allowed in labels (lower left plot).