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"This book provides an introduction to the field of microeconometrics through the use of R. The focus is on applying current learning from the field to real world problems. It uses R to both teach the concepts of the field and show the reader how the techniques can be used. It is aimed at the general reader with the equivalent of a bachelor's degree in economics, statistics or some more technical field. It covers the standard tools of microeconometrics, OLS, instrumental variables, Heckman selection and difference in difference. In addition, it introduces bounds, factor models, mixture models and empirical Bayesian analysis."

Preface -- Introduction -- Data objects in R -- Data handling in R -- R programming & control flow -- Data exploration -- Graphics in R -- Regression analysis-1 -- Regression analysis-ii -- Time series analysis -- Extreme value theory modelling -- Introduction to multivariate analysis using copulas -- Bibliography -- Index

Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. This book discusses advanced statistical methods that can be used to analyse ecological data. It revises regression, GAM and GLM, and discusses dealing with spatial or temporal dependencies and nested data

Many students learn to analyze data using commercial packages, even though there is an open-source software with cutting-edge possibilities: R, a programming language with countless cool features for applied empirical research. Practice R introduces R to social science students, inspiring them to consider R as an excellent choice. In a non-technical pragmatic way, this book covers all typical steps of applied empirical research. Learn how to prepare, analyze, and visualize data in R. Discover how to collect data, generate reports, or automate error-prone tasks. The book is accompanied by an R package. This provides further learning materials that include interactive tutorials, challenging you with typical problems of applied research. This way, you can immediately practice the knowledge you have learned. The package also includes the source code of each chapter and templates that help to create reports. Practice R has social science students in mind, nonetheless a broader audience may use Practice R to become a proficient R user.

"This book is built on the premise that anyone can learn to use the R software. The authors emphasize using R to do useful things like writing papers and reports, creating graphs, and conducting simple data analysis. After a first chapter on installing the software and project setup, the second chapter shows how to write an essay using R Markdown, rewarding readers with an immediate tangible result, and taking the fear out of working with a new software. Student-friendly language and examples (e.g. binge-watched shows on Netflix, top 5 songs on Spotify), cumulative learning and repetition across chapters, and practice exercises make this a must-have guide for a variety of courses where data is used and reports need to be written (including, but not limited to intro statistics and research methods). Code and datasets used to carry out the examples in the book are available on an accompanying website"--