Programming Books

33 Excellent Free Books to Learn all about R

Last Updated on May 4, 2023

26. Modern Statistics for Modern Biology by Susan Holmes & Wolfgang Huber

Modern-Statistics-for-Modern-BiologyModern Statistics for Modern Biology is targeted at biologists wanting to learn powerful methods of modern computational statistics.

It teaches you how to take raw data and turn it into informative and alluring output by learning how to write R scripts and to use advanced statistical packages from CRAN and Bioconductors.

The book covers a broad range of basic and advanced topics important in the analysis of high-throughput biological data, including principal component analysis and multidimensional scaling, clustering, multiple testing, unsupervised and supervised learning, resampling, the pitfalls of experimental design, and power simulations using Monte Carlo.

Read the book

27. Report Writing for Data Science in R by Roger D. Peng

Report-Writing-Data-Science-RThis book teaches the concepts and tools behind reporting modern data analyses in a reproducible manner.

Reproducibility is the idea that data analyses should be published or made available with their data and software code so that others may verify the findings and build upon them.

The book has a suggested price of $10 but can be downloaded for free.

Read the book

28. An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

An Introduction to Statistical Learning with Applications in RThis book provides an introduction to statistical learning methods.

It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.

The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist.

Read the book

Other useful books include:

29. Introduction to Statistical Thinking (With R, Without Calculus) by Benjamin Yakir

Introduction to Statistical Thinking is designed for college students who are required to learn statistics, students with little background in mathematics and often no motivation to learn more.

The first part of the book deals with descriptive statistics and provides probability concepts that are required for the interpretation of statistical inference. Statistical inference is the subject of the second part of the book.

Read the book

Next page: Page 7 – A Little Book of R for Biomedical Statistics and more books

Pages in this article:
Page 1 – R for Data Science and more books
Page 2 – R Graphics Cookbook and more books
Page 3 – Fundamentals of Data Visualization and more books
Page 4 – Data Analysis for the Life Sciences and more books
Page 5 – An Introduction To R and more books
Page 6 – Modern Statistics for Modern Biology and more books
Page 7 – A Little Book of R for Biomedical Statistics and more books

All books in this series:

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COBOLCommon Business-Oriented Language
CoffeeScriptTranscompiles into JavaScript inspired by Ruby, Python and Haskell
CoqDependently typed language similar to Agda, Idris, F* and others
CrystalGeneral-purpose, concurrent, multi-paradigm, object-oriented language
CSSCSS (Cascading Style Sheets) specifies a web page’s appearance
DGeneral-purpose systems programming language with a C-like syntax
DartClient-optimized language for fast apps on multiple platforms
DylanMulti-paradigm language supporting functional and object-oriented coding
ECMAScriptBest known as the language embedded in web browsers
EiffelObject-oriented language designed by Bertrand Meyer
ElixirRelatively new functional language running on the Erlang virtual machine
ErlangGeneral-purpose, concurrent, declarative, functional language
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FactorDynamic stack-based programming language
ForthImperative stack-based programming language
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GoCompiled, statically typed programming language
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HTMLHyperText Markup Language
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JavaGeneral-purpose, concurrent, class-based, object-oriented, high-level language
JavaScriptInterpreted, prototype-based, scripting language
JuliaHigh-level, high-performance language for technical computing
KotlinMore modern version of Java
LabVIEWDesigned to enable domain experts to build power systems quickly
LaTeXProfessional document preparation system and document markup language
LispUnique features - excellent to study programming constructs
LogoDialect of Lisp that features interactivity, modularity, extensibility
LuaDesigned as an embeddable scripting language
MarkdownPlain text formatting syntax designed to be easy-to-read and easy-to-write
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OCamlThe main implementation of the Caml language
PascalImperative and procedural language designed in the late 1960s
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PHPPHP has been at the helm of the web for many years
PostScriptInterpreted, stack-based and Turing complete language
PrologA general purpose, declarative, logic programming language
PureScriptSmall strongly, statically typed language compiling to JavaScript
PythonGeneral-purpose, structured, powerful language
QMLHierarchical declarative language for user interface layout - JSON-like syntax
RDe facto standard among statisticians and data analysts
RacketGeneral-purpose, object-oriented, multi-paradigm, functional language
RakuMember of the Perl family of programming languages
RubyGeneral purpose, scripting, structured, flexible, fully object-oriented language
RustIdeal for systems, embedded, and other performance critical code
ScalaModern, object-functional, multi-paradigm, Java-based language
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ValaObject-oriented language, syntactically similar to C#
VHDLHardware description language used in electronic design automation
VimLPowerful scripting language of the Vim editor
XMLRules for defining semantic tags describing structure ad meaning
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