Statistics Slam Dunk: Statistical analysis with R on real...

Statistics Slam Dunk: Statistical analysis with R on real NBA data

Gary Sutton
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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.
 
Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you’ll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions.
 
In Statistics Slam Dunk you’ll develop a toolbox of R programming skills including:
• Reading and writing data
• Installing and loading packages
• Transforming, tidying, wrangling data
• Applying best-in-class exploratory data analysis techniques
• Creating compelling visualizations
• Developing supervised and unsupervised machine learning algorithms
• Executing hypothesis tests, including t-tests and chi-square tests for independence
• Computing expected values, Gini coefficients,  z-scores, and other measures
 
If you’re looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner’s guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you’ll get no clean pre-packaged data sets in Statistics Slam Dunk. 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 reader
For readers who know basic statistics. No advanced knowledge of R—or basketball—required
 
About the author
Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals
Jahr:
2024
Auflage:
1
Verlag:
Manning Publications
Sprache:
english
Seiten:
672
ISBN 10:
1633438686
ISBN 13:
9781633438682
Datei:
PDF, 16.76 MB
IPFS:
CID , CID Blake2b
english, 2024
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