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Statistics with R

Statistics with R
A Beginner's Guide

Additional resources:

January 2018 | 392 pages | SAGE Publications Ltd

***Choice Outstanding Academic Title Award Winner***

The dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to:

  • Complete an introductory course in statistics
  • Prepare for more advanced statistical courses
  • Gain the transferable analytical skills needed to interpret research from across the social sciences
  • Learn the technical skills needed to present data visually
  • Acquire a basic competence in the use of R.  

The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions.

Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.

Chapter 1: Introduction and R Instructions
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
Chapter 3: Descriptive Statistics: Numerical Methods
Chapter 4: Introduction to Probability
Chapter 5: Discrete Probability Distributions
Chapter 6: Continuous Probability Distributions
Chapter 7: Point Estimation and Sampling Distributions
Chapter 8: Confidence Interval Estimation
Chapter 9: Hypothesis Tests: Introduction, Basic Concepts, and an Example
Chapter 10: Hypothesis Tests About u and p: Applications
Chapter 11: Comparisons of Means and Proportions
Chapter 12: Simple Linear Regression
Chapter 13: Multiple Regression


Click for online resources

For students

Author-made screencasts give you deeper insight into the key statistical ideas and R functions discussed in each chapter and show you first-hand how to work through some of the examples in the book.  The RStudio projects the author used in the screencasts are also available so you can follow along on your own computer.

Datasets and all R Scripts from the book ready to upload into R and RStudio generate meaningful information to help you master your statistics and data analysis skills.

Exercises and multiple choice questions test your knowledge of key concepts and provide a helpful revision tool for assignments and exams while the answers to in-text exercises allow you to check your work and make sure you’re on track.


For instructors

PowerPoint slides featuring figures, tables, and key topics from the book can be downloaded and customized for use in your own presentations.

Exercise testbanks containing questions related to the key concepts in each chapter can be downloaded and used in class or for homework and exams. 


Robert Stinerock provides a much-needed, easy-to-follow introduction to statistics and the R programming language. Any reader wishing to master and implement the statistical methods needed to derive meaning from data in today’s challenging information-rich environment will benefit from this insightful, exciting, and profoundly useful text.

Morris B. Holbrook
W. T. Dillard Professor Emeritus of Marketing, Columbia University

The ability to code, analyze, and derive insights from vast amounts of data are critical skills in today’s world of big data. This well-written book provides an excellent introduction to statistics and R programming language.

Sunil Gupta
Edward W. Carter Professor of Business, Harvard Business School

The book provides an excellent guide to statistics and the R programming language for beginners. Its wide range is exceptional to meet readers' needs in the era of big data and data science being the future. Brilliant!

Shaomin Wu
Reader in Business/Applied Statistics, University of Kent

The real added value is in the extensive use of R coding examples to illustrate and apply the principles in each section. For example, after a comprehensive description of simple linear regression modelling and some useful illustrative cases, the reader is provided with the code required to apply the technique to a real data set in R.

Jason Lowther
West Midlands Combined Authority
SRA Research Matters

The content is well structured and starts ‘right from the scratch’ which is especially useful for students getting into touch with R for the first time. Explicitly listing and explaining commands makes it easy to directly implement what has been learned. Furthermore, the summaries at the end of each chapter make achievement control easy and exercises further consolidate the acquired knowledge. Additionally, the statistical basis for the R commands is also explained in an illustrative yet scientifically suitable way.
As we are intending to encourage students to also take R into consideration when calculating, this book is a big help and will be a definite recommendation in my course!

Mr Philipp Kruse
Psychology, TU Dresden
February 14, 2018

It's very easy to read and allows a complete beginner to find their way through the process of R programming. A very much needed book.

Dr Magdalena Marczak
Faculty of Health & Life Sciences, Coventry University
July 6, 2018

Sample Materials & Chapters

Introduction and R Instructions