Superforecasting
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NEW YORK TIMES BESTSELLER * NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST "The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow."--Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week's meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts' predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people--including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer--who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They've beaten other benchmarks, competitors, and prediction markets. They've even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden's compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn't require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future--whether in business, finance, politics, international affairs, or daily life--and is destined to become a modern classic.
Sport Industry Research and Analysis
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Sport Industry Research and Analysis offers a straightforward, no nonsense approach to research design and statistical analyses in sport organizations. This fully revised and updated new edition describes the research process, from identifying a research question to analyzing data, and uses real world scenarios to help students and industry professionals understand how to conduct research and apply the results in their wider work. The book includes clear, step-by-step instructions for the analysis and interpretation of data. It explains how to use Excel and SPSS for every key statistic and statistical technique, with screenshots illustrating every step and additional scenarios providing further context. "In Practice" contributions from sport industry professionals demonstrate how these practitioners use statistical analyses in their everyday tasks, and this new edition includes expanded sections on conducting a literature review and research ethics, as well as ancillary materials for instructors including slides, test questions, data files, answer sheets, and videos. This is the clearest and most easy-to-use guide to research and analysis techniques in sport, helping the reader to build essential skills and confidence in using statistics, vital to support decision-making in any sport enterprise. It is an essential text for any sport business research methods course, and an invaluable reference for all sport industry professionals.
Handbook of Statistical Methods and Analyses in Sports
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This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer) followed by a section on other sports and general statistical design and analysis issues that are common to all sports. This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area.
Doing a Research Project in Sport Performance Analysis
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The research project or dissertation is a core component of any degree programme in the rapidly developing discipline of sport performance analysis. This highly practical and accessible book provides a complete step-by-step guide to doing a research project. Showcasing the very latest research methods, it covers the whole research process, from identifying a research question and system development to data collection, data analysis and writing up the results. Introducing the fundamentals of project planning and management, this book highlights the importance of research ethics and explains the differences between successful undergraduate and postgraduate projects. Full of expert advice and original insights that can be applied to theoretical and empirical research projects, it covers all the key aspects of conducting a degree-level research project, including: selecting a research topic and writing a research proposal working with a supervisor understanding research ethics implementing best practices for project management collecting, interpreting and presenting results. Doing a Research Project in Sport Performance Analysis is an indispensable guide for any student, lecturer or practitioner working in sport performance analysis.
Building a Platform for Data-Driven Pandemic Prediction
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This book is about building platforms for pandemic prediction. It provides an overview of probabilistic prediction for pandemic modeling based on a data-driven approach. It also provides guidance on building platforms with currently available technology using tools such as R, Shiny, and interactive plotting programs. The focus is on the integration of statistics and computing tools rather than on an in-depth analysis of all possibilities on each side. Readers can follow different reading paths through the book, depending on their needs. The book is meant as a basis for further investigation of statistical modelling, implementation tools, monitoring aspects, and software functionalities. Features: A general but parsimonious class of models to perform statistical prediction for epidemics, using a Bayesian approach Implementation of automated routines to obtain daily prediction results How to interactively visualize the model results Strategies for monitoring the performance of the predictions and identifying potential issues in the results Discusses the many decisions required to develop and publish online platforms Supplemented by an R package and its specific functionalities to model epidemic outbreaks The book is geared towards practitioners with an interest in the development and presentation of results in an online platform of statistical analysis of epidemiological data.　The primary audience includes applied statisticians, biostatisticians, computer scientists, epidemiologists, and professionals interested in learning more about epidemic modelling in general, including the COVID-19 pandemic, and platform building. The authors are professors at the Statistics Department at Universidade Federal de Minas Gerais. Their research records exhibit contributions applied to a number of areas of Science, including Epidemiology. Their research activities include books published with Chapman and Hall/CRC and papers in high quality journals. They have also been involved with academic management of graduate programs in Statistics and one of them is currently the President of the Brazilian Statistical Association.　
You can always try searching the William and Mary Libraries catalog and then narrow the Material Type to books, book chapters, or reference entries (this video is a refresher on searching the catalog; some of the details are different but the process remains the same). However, some of the specific background resources below may also be useful.
