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Mathletics

Author: Wayne L. Winston
Publisher: Princeton University Press
ISBN: 1400842077
Size: 55.97 MB
Format: PDF
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Mathletics is a remarkably entertaining book that shows readers how to use simple mathematics to analyze a range of statistical and probability-related questions in professional baseball, basketball, and football, and in sports gambling. How does professional baseball evaluate hitters? Is a singles hitter like Wade Boggs more valuable than a power hitter like David Ortiz? Should NFL teams pass or run more often on first downs? Could professional basketball have used statistics to expose the crooked referee Tim Donaghy? Does money buy performance in professional sports? In Mathletics, Wayne Winston describes the mathematical methods that top coaches and managers use to evaluate players and improve team performance, and gives math enthusiasts the practical tools they need to enhance their understanding and enjoyment of their favorite sports--and maybe even gain the outside edge to winning bets. Mathletics blends fun math problems with sports stories of actual games, teams, and players, along with personal anecdotes from Winston's work as a sports consultant. Winston uses easy-to-read tables and illustrations to illuminate the techniques and ideas he presents, and all the necessary math concepts--such as arithmetic, basic statistics and probability, and Monte Carlo simulations--are fully explained in the examples. After reading Mathletics, you will understand why baseball teams should almost never bunt, why football overtime systems are unfair, why points, rebounds, and assists aren't enough to determine who's the NBA's best player--and much, much more. In a new epilogue, Winston discusses the stats and numerical analysis behind some recent sporting events, such as how the Dallas Mavericks used analytics to become the 2011 NBA champions.

Grundlagen Und Technologien Des Ottomotors

Author: Helmut Eichlseder
Publisher: Springer Science & Business Media
ISBN: 3211257748
Size: 74.91 MB
Format: PDF, ePub, Mobi
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Die Autoren aus Wissenschaft und Industrie beschreiben alle wesentlichen funktionellen Bereiche des modernen Ottomotors. Detailliert erläutern sie Theorie und Praxis, Gemischbildungsverfahren und Gemischbildner anhand praktischer Beispiele. Dabei gehen sie von den Rahmenbedingungen und verwendeten Kraftstoffen aus, die die Entwicklung bestimmen. Neben der Fremdzündung (Schadstoffbildung, Abgasnachbehandlung) behandeln sie aktuelle Entwicklungen mit homogener Selbstzündung. Der Schwerpunkt des Buches liegt auf etablierten Ottomotor-Technologien, die bereits in Serie gingen. Plus: aktuelle Ansätze der Entwicklung und zahlreiche Abbildungen.

Analytic Methods In Sports

Author: Thomas A. Severini
Publisher: CRC Press
ISBN: 1482237024
Size: 67.94 MB
Format: PDF, ePub, Docs
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The Most Useful Techniques for Analyzing Sports Data One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analysis. Requiring familiarity with mathematics but no previous background in statistics, the book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter.

The Oxford Handbook Of Sports Economics Volume 2

Author: Leo H. Kahane
Publisher: Oxford University Press
ISBN: 0195387783
Size: 34.93 MB
Format: PDF, ePub, Docs
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Shmanske and Kahane have organized over 50 essays from prominent Sports Economists into two volumes around two related themes. This second volume explains how sports helps economics via quality data used to test a variety of economic theories.

Stumbling On Wins Bonus Content Edition

Author: David Berri
Publisher: Pearson Education
ISBN: 9780137069514
Size: 22.11 MB
Format: PDF, ePub, Docs
View: 1960
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The next quantum leap beyond Moneyball , this book offers powerful new insights into all human decision-making, because if sports teams are getting it wrong this badly, how do you know you're not? Sometimes the decisions that teams make are simply inexplicable. Consider: sports teams have an immense amount of detailed, quantifiable information to draw upon, more than in virtually any other industry. They have powerful incentives for making good decisions. Everyone sees the results of their choices, and the consequences for failure are severe. And yet... they keep making the same mistakes over and over again... systematic mistakes you'd think they'd learn how to avoid. Now, two leading sports economists reveal those mistakes in basketball, baseball, football, and hockey, and explain why sports decision-makers never seem to learn their lessons. You'll learn which statistics are connected to wins, and which aren't, and which statistics can and can't predict the future. Along the way, David Berri and Martin Schmidt show why a quarterback's place in the draft tells you nothing about how he'll perform in the NFL... why basketball decision-makers don't focus on the factors that really correlate with NBA success... why famous coaches don't deliver better results... and much more.

Statistik Mit Excel F 1 4r Dummies

Author: Joseph Schmuller
Publisher: John Wiley & Sons
ISBN: 3527811702
Size: 35.86 MB
Format: PDF, ePub, Docs
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Statistiken und Aussagen zu Wahrscheinlichkeiten begegnen uns heute ï¿1⁄2berall: Die Umsatzentwicklung in Unternehmen, Hochrechnungen fï¿1⁄2r Wahlergebnisse, PISA-Ergebnisse fï¿1⁄2nfzehnjï¿1⁄2hriger Schï¿1⁄2ler sind nur drei von zahlreichen Beispielen. Joseph Schmuller zeigt Ihnen in diesem Buch, wie Sie die Zahlen in den Griff bekommen und Daten, Statistiken und Wahrscheinlichkeiten richtig lesen und interpretieren. Dafï¿1⁄2r brauchen Sie keinen Statistikkurs zu belegen und kein Mathegenie zu sein. Fï¿1⁄2r alles gibt es in Excel die passende Funktion und das passende Werkzeug. So kï¿1⁄2nnen Sie Theorie und Praxis sofort miteinander verbinden.

Modeling Techniques In Predictive Analytics

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133886190
Size: 31.17 MB
Format: PDF, ePub
View: 227
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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Statistik Ii F R Dummies

Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
ISBN: 3527669248
Size: 28.69 MB
Format: PDF, Kindle
View: 6921
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Es gibt Qualen, verdammte Qualen und Statistik, so sehen es viele Studenten. Mit ?Statistik II f?r Dummies? lernen Sie so leicht wie m?glich. Deborah Rumsey zeigt Ihnen, wie Sie Varianzanalysen und Chi-Quadrat-Test machen, wie Sie mit Regressionen arbeiten, ein Modell erstellen, Korrelationen bilden und vieles mehr. So lernen Sie die Methoden, die Sie brauchen, und erhalten das Handwerkszeug, erfolgreich Ihre Statistikpr?fungen zu bestehen.

Modeling Techniques In Predictive Analytics With Python And R

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Size: 61.24 MB
Format: PDF, Mobi
View: 5719
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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more