Modern Statistics with R
From wrangling and exploring data to inference and predictive modelling
2021-06-07 - Draft version 0.9.13
This is the online version of the book Modern Statistics with R. It is free to use, and always will be. Printed copies will be available in the (Northern hemisphere) summer of 2021.
The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you:
- Data wrangling - importing, formatting, reshaping, merging, and filtering data in R.
- Exploratory data analysis - using visualisations and multivariate techniques to explore datasets.
- Statistical inference - modern methods for testing hypotheses and computing confidence intervals.
- Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting.
- Simulation - using simulation techniques for sample size computations and evaluations of statistical methods.
- Ethics in statistics - ethical issues and good statistical practice.
- R programming - writing code that is fast, readable, and (hopefully!) free from bugs.
The book includes plenty of examples and more than 200 exercises with worked solutions.
Navigate the book using the menu to the left.
The digital version of the book is offered under the Creative Commons CC BY-NC-SA 4.0. license, meaning that you are free to redistribute and build upon the material for noncommercial purposes, as long as appropriate credit is given to the author.