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, and 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
Autorentext
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.