Title: introduction to data science and statistical programming in R
Author: Thomas Mailun
Publication date: 2016

Modern data analysis requires computational skills and usually a minimum of programming. The R programming language provides an ideal environment for developing these skills. This book teaches you best practises both for data analysis and software development in R and sets you on the path to becoming a full fledged data scientist.

Data science is a combination of statistics, computational science and machine learning. In data science your goal is to efficiently structure and mine data in order to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. The R programming language is a domain specific language aimed at statistical methods and the R environment contains many packages for common machine learning methods.

The book requires no previous knowledge of the R programming language but teaches best practises for both data manipulation and visualisation and for developing new software packages for R .

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