Modern Statistics with R

<p>The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. <i>Modern Statistics with R</i> introduces you to key parts of this modern statistical toolkit. It teaches you:</p><ul><li><b>Data wrangling</b> – importing, formatting, reshaping, merging, and filtering data in R.</li><li><b>Exploratory data analysis</b> – using visualisations and multivariate techniques to explore datasets.</li><li><b>Statistical inference</b> – modern methods for testing hypotheses and computing confidence intervals.</li><li><b>Predictive modelling</b> – regression models and machine learning methods for prediction, classification, and forecasting.</li><li><b>Simulation</b> – using simulation techniques for sample size computations and evaluations of statistical methods.</li><li><b>Ethics in statistics</b> – ethical issues and good statistical practice.</li><li><b>R programming</b> – writing code that is fast, readable, and (hopefully!) free from bugs.</li></ul><p>No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book.</p><p>In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.</p>