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"The Third Edition of An R Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students to conduct political research with R, the open source programming language and software environment for statistical computing and graphics. This workbook offers the same easy-to-use and effective style as other software Companions, tailored for R. With this comprehensive workbook, students analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (such as cross-tabulations and mean comparisons), controlled comparisons, correlation and bivariate regression, interaction effects, and logistic regression. The clear explanations and instructions are aided by the use of many annotated and labeled screen shots, as well as QR codes linking to demonstration videos. The many end-of-chapter exercises allow students to apply their new skills. The Third Edition includes new and revised exercises, along with new and updated datasets from the 2020 American National Election Study, an experiment dataset, and two aggregate datasets, one on 50 U.S. states and one based on countries of the world. A new structure helps break up individual elements of political analysis for deeper explanation while an updated suite of R functions makes using R even easier. Students will gain valuable skills learning to analyze political data in R"--

"This first edition of Statistics Using R: An Integrative Approach capitalizes on the versatility and power of the R software package to create a course of study that links good statistical and data science practice to the analysis of real data. It also benefits from the many years of the authors' experience teaching statistics to undergraduate students at a liberal arts university and to undergraduate and graduate students at a large research university from a variety of disciplines including education, psychology, health, and policy analysis. Because R, a free, open-source software, provides a command line approach to the analysis of data, and, in so doing, this textbook teaches readers the skills necessary to program statistical analyses"--

The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science.

The Preliminaries. Why R? -- The R Basics -- Data Preparation and Other Tricks -- Exploratory Data Analysis -- Probability and Inference. Probability Theory -- Probability and Sampling Distributions -- Parametric Inference -- Nonparametric Inference -- Bayesian Inference -- Stochastic Processes and Monte Carlo. Stochastic Processes -- Monte Carlo Computations -- Linear Models. Linear Regression Models -- Experimental Designs -- Multivariate Statistical Analysis - I -- Multivariate Statistical Analysis - II -- Categorical Data Analysis -- Generalized Linear Models -- Appendix A: Open Source Software: An Epilogue -- Appendix B: The Statistical Tables

R in Action, Third Edition makes learning R quick and easy. That's why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you'll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R's state-of-the-art graphing capabilities with the ggplot2 package

Praise for the First Edition " ... an excellent addition to an upper-level undergraduate course on environmental statistics, and ... a 'must-have' desk reference for environmental practitioners dealing with censored datasets."--Vadose Zone Journal Statistical Methods for Censored Environmental Data Using Minitab® and R, Second Edition introduces and explains methods for analyzing and interpreting censored data in the environmental sciences. Adapting survival analysis techniques from other fields, the book translates well-established methods from other disciplines into new solutions for en

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham's package development philosophy. In the process, you'll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language.Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You'll learn to focus on what you want your package to do, rather than think about package structure. Learn about the most useful components of an R package, including vignettes and unit testsAutomate anything you can, taking advantage of the years of development experience embodied in devtoolsGet tips on good style, such as organizing functions into filesStreamline your development process with devtoolsLearn the best way to submit your package to the Comprehensive R Archive Network (CRAN)Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr

"Individual-Based Models of Cultural Evolution shows readers how to create individual-based models of cultural evolution using the programming language R. The field of cultural evolution has emerged in the last few decades as a thriving, interdisciplinary effort to understand cultural change and cultural diversity within an evolutionary framework and using evolutionary tools, concepts and methods"--