Slam Dunk 2

The game of basketball involves speed, strength, and skill—and numbers. Readers learn the many ways that math is used in b-ball, from keeping score to comparing players. Quizzes on each page help readers practice math skills just like basketball players practice their skills.

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 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. Foreword by Thomas W. Miller. About the technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through—from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you’ll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You’ll answer all these questions and more. Plus, R’s visualization capabilities shine through in the book’s 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. 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. Table of Contents 1 Getting started 2 Exploring data 3 Segmentation analysis 4 Constrained optimization 5 Regression models 6 More wrangling and visualizing data 7 T-testing and effect size testing 8 Optimal stopping 9 Chi-square testing and more effect size testing 10 Doing more with ggplot2 11 K-means clustering 12 Computing and plotting inequality 13 More with Gini coefficients and Lorenz curves 14 Intermediate and advanced modeling 15 The Lindy effect 16 Randomness versus causality 17 Collective intelligence

Jeff Turner helps Buzz Star announce during a basketball championship game, in a story where the pronouns are highlighted within the text and explained using informational sidebars.

More than 100 can't-miss cover letters for any point along the career path.

In this marvelously original book, three-time Pulitzer Prize finalist Leslie Savan offers fascinating insights into why we’re all talking the talk—Duh; Bring it on!; Bling; Whatever!—and what this reveals about America today. Savan traces the paths that phrases like these travel from obscure slang to pop stardom, selling everything from cars (ads for VWs, Mitsubishis, and Mercurys all pitch them as “no-brainer”s) to wars (finding WMD in Iraq was to be a “slam dunk”). Real people create these catchy phrases, but once media, politics, and businesses broadcast them, they burst out of our mouths as celebrity words, newly glamorous and powerful. Witty, fun, and full of thought-provoking stories about the origins of popular expressions, Slam Dunks and No-Brainers is for everyone who loves the mysteries of language.

Motor games are incredibly useful in enhancing education and developing critical skills; they can entertain, produce pleasant emotions, improve moods, and increase the level of relationships. Motor games allow social, emotional, and cognitive development as well as the acquisition of motor skills such as knowledge and mastery of body, postural control and adjustment, and improvement of coordination. However, it is essential to select the appropriate game for each context to achieve the desired learning in all students. Further research on the opportunities, challenges, and future directions of motor games in education is necessary to successfully implement them. The Handbook of Research on Using Motor Games in Teaching and Learning Strategy presents significant advances in motor game education and collects research evidence that uncovers the certainties and testifies to the educational power of motor games in various situations and specific contexts that promote the learning of participants. Covering topics such as emotional physical education and educational mediation, this major reference work is ideal for researchers, academicians, educators, practitioners, and students.