Statistics Playbook you own this product

Real NBA data using R
Gary Sutton
  • MEAP began September 2022
  • Publication in Summer 2023 (estimated)
  • ISBN 9781633438682
  • 500 pages (estimated)
  • printed in black & white
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An excellent way to learn exploratory data analysis and statistical analysis with R and sports statistics from the NBA.

Bob Quintus
Look inside
Learn statistics by analyzing professional basketball data! In this action-packed book, you’ll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language.

In Statistics Playbook you’ll develop a toolbox of R data skills including:

  • Reading and writing data
  • Installing and loading packages
  • Transforming, tidying, and wrangling data
  • Applying best-in-class exploratory data analysis techniques
  • Creating compelling visualizations
  • Developing supervised and unsupervised machine learning algorithms
  • Execute hypothesis tests, including t-tests and chi-square tests for independence
  • Compute expected values, Gini coefficients, and z-scores

Statistics Playbook upgrades your R data science skills by taking on practical analysis challenges based on NBA game and player data. Is losing games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Each chapter in this one-of-a-kind guide uses new data science techniques to reveal interesting insights like these. And just like in the real world, you’ll get no clean pre-packaged datasets in Statistics Playbook. You’ll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team.

about the technology

Amazing insights are hiding in raw data, and statistical analysis with R can help reveal them! R was built for data, and it supports modeling and statistical techniques including regression and classification models, time series forecasts, and clustering algorithms. And when you want to see your results, R’s visualizations are stunning, with best-in-class plots and charts.

about the book

Statistics Playbook is an interesting and engaging how-to guide for statistical analysis using R. It’s packed with practical statistical techniques, each demonstrated using real-world data taken from NBA games. In each chapter, you’ll discover a new (and sometimes surprising!) insight into basketball, with careful step-by-step instructions on how to generate those revelations.

You’ll get practical experience cleaning, manipulating, exploring, testing, and otherwise analyzing data with base R functions and useful R packages. R’s visualization capabilities shine through in the book’s 300 visualizations, and almost 30 plots and charts including Pareto charts and Sankey diagrams. Much more than a beginner’s guide, this book explores advanced analytics techniques and data wrangling packages. You’ll find yourself returning again and again to use this book as a handy reference!

about the reader

Requires a beginning knowledge of basic statistics concepts. No advanced knowledge of statistics, machine learning, R–or basketball–required.

about the author

Gary Sutton is a vice president for a leading financial services company. He has built and led high-performing business intelligence and analytics organizations across multiple verticals, where R was the preferred programming language for predictive modeling, statistical analyses, and other quantitative insights. Gary earned his undergraduate degree from the University of Southern California, a Masters from George Washington University, and a second Masters in Data Science, from Northwestern University.

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This book is very impressive. Different from other similar books, this book integrates the technology of R language through storytelling.

Chen Sun

A great example of using R and applying it to a machine learning problem.

John Williams

Very interesting subject matter. The author’s enthusiasm for it really shows.

Lachman Dhalliwal

For users looking to get experience with real world datasets, this book will provide a great methodological approach.

Eli Mayost