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 visualisation 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 free from bugs.
Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions.
Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.
