Doing Data Science in R

Mark Andrews (PhD) is Senior Lecturer in the Department of Psychology in Nottingham Trent University. There, he specializes in teaching statistics and data science at all levels from undergraduate to PhD level. Currently, he is the Chair of the British Psychological Society's Mathematics, Statistics, and Computing section. Between 2015 and 2018, Dr Andrews was funded by the UK's Economic and Social Research Council (ESRC) to provide advanced training workshop on Bayesian data analysis to UK based researchers at PhD level and beyond in the social sciences. Dr Andrews's background is in computational cognitive science, particularly focused Bayesian models of human cognition. He has a PhD in Cognitive Science from Cornell University, and was a postdoctoral researcher in the Gatsby Computational Neuroscience Unit in UCL and also in the Department of Psychology in UCL.

Chapter 1: Data Analysis And Data Science Chapter 2: Introduction To R Chapter 3: Data Wrangling Chapter 4: Data Visualization Chapter 5: Exploratory Data Analysis Chapter 6: Programming In R Chapter 7: Reproducible Data Analysis Chapter 8: Statistical Models and Statistical Inference Chapter 9: Normal Linear Models Chapter 10: Logistic Regression Chapter 11: Generalized Linear Models for Count Data Chapter 12: Multilevel Models Chapter 13: Nonlinear Regression Chapter 14: Structural Equation Modelling Chapter 15: High Performance Computing with R Chapter 16: Interactive Web Apps with Shiny Chapter 17: Probabilistic Modelling with Stan

This book will be extremely useful for advanced UG's along with those on PGT courses. It will also be an excellent handbook for PGR students. It's perfect for those taking their first serious steps into becoming actively involved in research employing tools in R. -- Eugene McSorley Mark Andrews has written a must-read primer for anyone using statistical techniques in their research. From introductory through to advanced techniques, an easy, intuitive and example driven book sure to get you the right answer. -- Jason Hay Doing Data science in R: An introduction for Social Scientists is one of the best available books to learn how to conduct serious empirical research via rigorous methods and techniques. The text is illustrated with many examples written in R and Stan, and is ideal either as a textbook or for self-study. -- Roula Nezi