Twenty-four million people wager nearly $3 billion on college basketball pools each year, but few are aware that winning strategies have been developed by researchers at Harvard, Yale, and other universities over the past two decades. Bad advice from media sources and even our own psychological inclinations are often a bigger obstacle to winning than our pool opponents. Profit opportunities are missed and most brackets submitted to pools don’t have a breakeven chance to win money before the tournament begins. Improving Your NCAA® Bracket with Statistics is both an easy-to-use tip sheet to improve your winning odds and an intellectual history of how statistical reasoning has been applied to the bracket pool using standard and innovative methods. It covers bracket improvement methods ranging from those that require only the information in the seeded bracket to sophisticated estimation techniques available via online simulations. Included are: Prominently displayed bracket improvement tips based on the published research A history of the origins of the bracket pool A history of bracket improvement methods and their results in play Historical sketches and background information on the mathematical and statistical methods that have been used in bracket analysis A source list of good bracket pool advice available each year that seeks to be comprehensive Warnings about common bad advice that will hurt your chances Tom Adams’ work presenting bracket improvement methods has been featured in the New York Times, Sports Illustrated, and SmartMoney magazine.

How do you learn about what’s going on in the world? Did a news headline grab your attention? Did a news story report on recent research? What do you need to know to be a critical consumer of the news you read? If you are looking to start developing your data self-defense and critical news consumption skills, this book is for you! It reflects a long-term collaboration between a statistician and a journalist to shed light on the statistics behind the stories and the stories behind the statistics. The only prerequisite for enjoying this book is an interest in developing the skills and insights for better understanding news stories that incorporate quantitative information. Chapters in Statistics Behind the Headlines kick off with a news story headline and a summary of the story itself. The meat of each chapter consists of an exploration of the statistical and journalism concepts needed to understand the data analyzed and reported in the story. The chapters are organized around these sections: What ideas will you encounter in this chapter? What is claimed? Is it appropriate? Who is claiming this? Why is it claimed? What makes this a story worth telling? Is this a good measure of impact? How is the claim supported? What evidence is reported? What is the quality/strength of the evidence? Does the claim seem reasonable? How does this claim fit with what is already known? How much does this matter? Considering the coverage Chapters close with connections to the Stats + Stories podcast.

Statistics and Health Care Fraud: How to Save Billions helps the public to become more informed citizens through discussions of real world health care examples and fraud assessment applications. The author presents statistical and analytical methods used in health care fraud audits without requiring any mathematical background. The public suffers from health care overpayments either directly as patients or indirectly as taxpayers, and fraud analytics provides ways to handle the large size and complexity of these claims. The book starts with a brief overview of global healthcare systems such as U.S. Medicare. This is followed by a discussion of medical overpayments and assessment initiatives using a variety of real world examples. The book covers subjects as: • Description and visualization of medical claims data • Prediction of fraudulent transactions • Detection of excessive billings • Revealing new fraud patterns • Challenges and opportunities with health care fraud analytics Dr. Tahir Ekin is the Brandon Dee Roberts Associate Professor of Quantitative Methods in McCoy College of Business, Texas State University. His previous work experience includes a working as a statistician on health care fraud detection. His scholarly work on health care fraud has been published in a variety of academic journals including International Statistical Review, The American Statistician, and Applied Stochastic Models in Business and Industry. He is a recipient of the Texas State University 2018 Presidential Distinction Award in Scholar Activities and the ASA/NISS y-Bis 2016 Best Paper Awards. He has developed and taught courses in the areas of business statistics, optimization, data mining and analytics. Dr. Ekin also serves as Vice President of the International Society for Business and Industrial Statistics.

At what point does the sacrifice to our personal information outweigh the public good? If public policymakers had access to our personal and confidential data, they could make more evidence-based, data-informed decisions that could accelerate economic recovery and improve COVID-19 vaccine distribution. However, access to personal data comes at a steep privacy cost for contributors, especially underrepresented groups. Protecting Your Privacy in a Data-Driven World is a practical, nontechnical guide that explains the importance of balancing these competing needs and calls for careful consideration of how data are collected and disseminated by our government and the private sector. Not addressing these concerns can harm the same communities policymakers are trying to protect through data privacy and confidentiality legislation.

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures. In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics: Advice on selecting prior distributions Computational methods including Markov chain Monte Carlo (MCMC) Model-comparison and goodness-of-fit measures, including sensitivity to priors Frequentist properties of Bayesian methods Case studies covering advanced topics illustrate the flexibility of the Bayesian approach: Semiparametric regression Handling of missing data using predictive distributions Priors for high-dimensional regression models Computational techniques for large datasets Spatial data analysis The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets, and complete data analyses are available on the book’s website. Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRoy & Elva Martin Teaching Award. Sujit K. Ghosh, Professor of Statistics at North Carolina State University, has over 22 years of research and teaching experience in conducting Bayesian analyses, received the Cavell Brownie mentoring award, and served as the Deputy Director at the Statistical and Applied Mathematical Sciences Institute.

Demonstrates how modern statistical techniques can measure the impact of counterfactual decisions. Examines the importance of counterfactual reasoning for both modern scholars and historical actors. Combines historical narrative, mathematical precision and data to create a straightforward presentation of both factual and counterfactual military history. Provides an original contribution to the debate over the validity and rigour of works of counterfactual history Written in a manner accessible to readers who have no formal training in History or Statistics.

Buying the safest car for your family shouldn’t be up for debate. Yet for decades, car safety advocates, manufacturers, and lawmakers in the United States have clashed over whether to make automobiles safer. All sides armed themselves with data in the hopes of winning the great car safety debates. In this way, crash statistics and the analysts who studied them made history. But data were always in the backseat, merely supporting different points of view. That is, until now. With car safety, it’s the value we place on every human life that counts. Automobile safety expert Dr. Norma Faris Hubele delivers a lively discussion of the role data play in protecting you and your family on the road. You’ll gain a greater appreciation for how: A World War I pilot’s near-death experience birthed the U.S. car safety movement Data from real car crashes helped create the first vehicle safety standards A shift toward fuel-efficient cars affected fatality risk in the 1970s–1980s versus now Vehicle size has changed, and the problems that creates for you and others sharing the road Car safety rating systems, even when limited, empower consumers and motivate manufacturers Federal regulators decide whether to issue a safety recall on your vehicle Data’s role is evolving with the advent of driver-assist and self-driving technologies Further information can be found on the book's website: www.TheAutoProfessor.com/book [US only].

Crime statistics are everywhere, but how do you know when they’re valid? If a newspaper report says "the rate of overall violent crime decreased by 0.9 percent," how can you tell where that statistic came from, what it measures, and how accurate it is? Is it worth repeating or sharing? Measuring Crime: Behind the Statistics gives you the tools to interpret and evaluate crime statistics’ quality and usefulness. The book focuses on ways of thinking about crime statistics (no formulas!) and features Eight questions you should ask before quoting a statistic The two sources of information about homicide FBI statistics: what do they measure? How victimization surveys can reflect your experiences even though you were not asked to participate Special considerations when interpreting statistics about sexual assault and fraud Examples of experiments and studies on how to improve crime statistics Two online supplements containing additional details and links to data sources Whether you are a law enforcement professional, journalist, student, or interested citizen, Measuring Crime: Behind the Statistics will tell you how to read statistics as a statistician would. Sharon Lohr, the author of Sampling: Design and Analysis, has published widely about statistical methods for education, public policy, law, and crime. She has been recognized as Fellow of the American Statistical Association, elected member of the International Statistical Institute, and recipient of the Gertrude M. Cox Statistics Award and the Deming Lecturer Award. Formerly Dean’s Distinguished Professor of Statistics at Arizona State University and a Vice President at Westat, she is now a freelance statistical consultant and writer. Visit her website at www.sharonlohr.com. "The book aims to achieve two goals: introduce statistical ideas to a general audience and provide an overview of US crime statistics. These are disparate topics, but in the way they are approached here, there is a strong synergy that reinforces both aspects. One the one hand, the reader's natural curiosity about crime (what is it, how are crime events classified and reported, how reliable are the numbers you see in the newspaper, etc.) will help him/her become interested in the statistical issues and learn these concepts in a practical and concrete setting. And on the other hand, by reading about the statistical issues surrounding crime data, he/she gains a better appreciation for the complexities of crime statistics, eventually acquiring a deeper understanding of them. As a statistician myself, I learned interesting facts about the types of crime, their nomenclature and the possible confusion surrounding them, and how the data are collected and reported. Overall, I think the combination is effective and very well developed in this book." (Jean Opsomer, Westat) "This book is an excellent primer on handling the mass of data and information researchers are faced with. While it is geared toward followers of criminal justice information, much of the book is a very good introduction to survey techniques discussing their strong and weak points. Most importantly, there are very good guidelines and questions that one should employ before citing any data or using data for policy decisions or for reporting on data such as journalists do. The book is written in a non-technical manner and does a very good job of explaining the nuances in reviewing data. Any researcher who utilizes data would find this valuable. While it has specific examples in the criminal justice field, it really is quite useful for any user of data." (Barry Nussbaum, former President American Statistical Association)

Are you buying a car or smartphone or dishwasher? We bet long-term, trouble-free operation (i.e., high reliability) is among the top three things you look for. Reliability problems can lead to everything from minor inconveniences to human disasters. Ensuring high reliability in designing and building manufactured products is principally an engineering challenge–but statistics plays a key role. Achieving Product Reliability explains in a non-technical manner how statistics is used in modern product reliability assurance. Features: Describes applications of statistics in reliability assurance in design, development, validation, manufacturing, and field tracking. Uses real-life examples to illustrate key statistical concepts such as the Weibull and lognormal distributions, hazard rate, and censored data. Demonstrates the use of graphical tools in such areas as accelerated testing, degradation data modeling, and repairable systems data analysis. Presents opportunities for profitably applying statistics in the era of Big Data and Industrial Internet of Things (IIoT) utilizing, for example, the instantaneous transmission of large quantities of field data. Whether you are an intellectually curious citizen, student, manager, budding reliability professional, or academician seeking practical applications, Achieving Product Reliability is a great starting point for a big-picture view of statistics in reliability assurance. The authors are world-renowned experts on this topic with extensive experience as company-wide statistical resources for a global conglomerate, consultants to business and government, and researchers of statistical methods for reliability applications.

Today the citizens of developed counties have never experienced a large-scale disease outbreak. One reason is the success of the public health community, including epidemiologists and biostatisticians, in tracking and identifying disease outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often critically depends on the use of statistical methods to help discern whether an outbreak may be occurring and, if there is sufficient evidence of an outbreak, then to locate and track it. Statisticians also help design surveys and experiments to collect critical information, and they analyze the resulting data to help investigators zero in on a cause for a disease. Features: · Discusses the crucial roles of statistics in early disease detection. · Outlines the concepts and methods of disease surveillance. · Covers surveillance techniques for communicable diseases like Zika and chronic diseases such as cancer. · Gives real world examples of disease investigations including smallpox, syphilis, anthrax, yellow fever, and microcephaly (and its relationship to the Zika virus). This book tells the story of how medical and public health professionals use statistics to separate critical disease information from all the noise of our modern world so that they can most effectively intervene and mitigate the effects of disease. Through the process of identifying an outbreak, finding its cause, and developing a plan to prevent its reoccurrence, statisticians and epidemiologists help improve public health across the world.