Data Analysis using R
What is R?
R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years.
Style Guide for R Programming
Install R - https://cran.r-project.org/ - This R core software.
Install RStudio Desktop - https://rstudio.staging.wpengine.com/products/RStudio/ - User friendly IDE for R
Both are open source software.
Basic of Statistics
It is thriving and rich source for R, machine learning related topics.
Common R packages
Data Science Resources:
UCLA’s IDRE collection of examples using R, SAS, SPSS, and Stata
Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani’s Introduction to Statistical Learning, with Applications in R.
Jeff Leek’s The Elements of Data Analytic Style.
Andrew Gelman’s Statistical Modeling, Causal Inference, and Social Science
Rafa Irizarry, Roger Peng, and Jeff Leek’s Simply Statistics
Nathan Yau’s Flowing Data
Randall Munroe’s xkcd
Dolph Schluter’s R tips pages at the University of BC
Rob Kabacoff’s Quick-R site
R-Bloggers, a digest of R news and tutorials contributed by R users
Mad (Data) Scientist, Norman Matloff’s personal blog on R and data science
RStudio’s library of cheatsheets