Books

Longitudinal Data Analysis Using R is a practical, end-to-end guide to longitudinal data analysis that helps you move from raw data to credible substantive conclusions. It tackles the real pain points researchers face in longitudinal analysis, such as data preparation, exploring change over time, model choice, missing data, and interpretation, using clear explanations, real-world data, and fully reproducible R code.

If you are an independent learner or an instructor for a data science, statistics, or public health course, check out the open case studies project (www.opencasestudies.org) and this guide which will describe the variety of ways our case studies can be used for hands-on data science activities.

Selected modern machine learning techniques and the intuition behind them. Methods are supplemented by code snippets with examples in R language. The process is shown through a comic book describing the adventures of two characters, Beta and Bit.  See the flipbook version at https://betaandbit.github.io/RML/

All statistical foundations you need to understand and use machine learning! It includes R/Pyhton software and Shiny dashboards to illustrate numerically the most important concepts.

Understanding the dynamics of populations is indispensable for conservation biologists. 'Using basic models in conservation biology' will help you to get a grasp of the fundamentals, and it will show you how to use and develop these aspects with the programming language R.

El complemento imprescindible del manual Fundamentos de R.

Este manual está dedicado íntegramente a los fundamentos de R y sólo a ellos. Se espera así complementar la formación de los científicos de datos, que disponen de cientos de manuales sobre análisis de datos con R pero apenas cuentan con manuales, completos, que fundamenten en detalle la herramienta a utilizar.

DataViz: How to Choose the Right Chart for Your Data is a short guide to all the different types of charts you’ll commonly encounter in statistics.It is a snappy little non-threatening book about everything you ever wanted to know about the craft of creating inspirational graphics for your study – irrespective of your audience.

The goal of this book is to get the reader up to speed with chart production with ggplot2. This book is the third in a series of books by the same author which deals with data visualization in R. Hope you enjoy it as we did writing it.

The goal of this book is to explore the nooks and crannies of chart production with the lattice package and is the second in a series of books on data visualization with R. Enjoy !!!

If there is one thing R is famous and known about, is its graphics capabilities. There are many packages out there for producing plots in R, top amongst which is the base graphics package which comes with R preinstalled.  The goal of this book is to explore chart production with base graphics in depth.

Interested in launching a personal website, blog, or project portfolio? Take this opportunity to learn the step-by-step process to create, design, publish, and analyze your website using R and many other open source technologies.

Although this book is not a comprehensive text that covers every single aspect about creating R packages, I’ve written it in the spirit of an extended tutorial or guide document with a relatively simple working example.

This book aims to help you get started with handling strings in R. It provides an overview of several resources that you can use for string manipulation. It covers useful functions in packages "base" and "stringr", printing and formatting characters, regular expressions, and other tricks.

Data wrangling is one of the most important steps in data science and analytics, for it is claimed that it takes between 80% to 90% of an analyst’s time. Data wrangling goes by many names including data munging, data manipulation, data preparation and data transformations. This book is all about data wrangling and exploration with R.