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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Chapman and Hall/CRC | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (334 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It equips readers with the necessary skills and software tools to perform all of the analysis steps, from gathering the datasets and entering them in a convenient format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the traditional graphics functions in the base package and introduce more sophisticated graphical displays available through the lattice and ggplot2 packages. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and fielding measures. Each chapter contains exercises that encourage readers to perform their own analyses using R. All of the datasets and R code used in the text are available online. This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. Through the book’s various examples, readers will learn about modern sabermetrics and be able to conduct their own baseball analyses.
    Note: Online resource; Title from title page (viewed January 17, 2018)
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  • 2
    Book
    Book
    New York [u.a.] :Springer,
    ISBN: 978-1-4614-1364-6
    Language: English
    Pages: XIII, 359 S. : , graph. Darst.
    Series Statement: Use R!
    Parallel Title: Erscheint auch als
    RVK:
    RVK:
    RVK:
    Keywords: R ; Einführung ; R
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  • 3
    Online Resource
    Online Resource
    New York, NY : Springer
    ISBN: 9780387215129
    Language: English
    Pages: Online-Ressource (XVIII, 350 p) , digital
    Edition: Springer eBook Collection. Humanities, Social Sciences and Law
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Science (General) ; Statistics ; Sports. ; Popular works. ; Probabilities. ; Mathematics. ; Sports sciences. ; Engineering. ; Life sciences. ; Social sciences. ; Humanities.
    Abstract: The intent of this book is to look at baseball data from a statistical modeling perspective. There is a fascination among baseball fans and the media to collect data on every imaginable event during a baseball game and to use these data to try to understand characteristics of the game. The problem is that patterns in baseball data are difficult to detect due to the inherent chance variation that is present. This book addresses a number of questions that are of interest to many baseball fans. These issues include how to rate players, predict the outcome of a game or the attainment of an attainment, making sense of situational data, and deciding the most valuable players in the World Series. This book will be directed to a general audience and does not assume that the reader has any prior background in probability or statistics, although knowledge of high school algebra will be helpful
    URL: Volltext  (lizenzpflichtig)
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  • 4
    Book
    Book
    New York [u.a.] :Springer,
    ISBN: 0-387-98718-5
    Language: German
    Pages: X, 258 S. : , graph. Darst.
    Series Statement: Statistics for social science and public policy
    DDC: 519.5 21
    RVK:
    RVK:
    RVK:
    Keywords: Data-analyse ; Ordinale gegevens ; Politieke wetenschappen ; Regressiemodellen ; Sociale wetenschappen ; Statistische methoden ; Sozialwissenschaften ; Social sciences -- Statistical methods ; Policy sciences -- Statistical methods ; Numbers, Ordinal ; Statistik. ; Sozialwissenschaften. ; Politische Wissenschaft. ; Statistik ; Sozialwissenschaften ; Politische Wissenschaft ; Statistik
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