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Books in Statistics

  • An Introduction to Applied Sport Analytics

    • 1st Edition
    • Jon Nachtigal + 1 more
    • English
    An Introduction to Applied Sport Analytics offers a step-by-step path for applying data-driven methods in sport. The book begins with the evolution of sport analytics and foundational concepts like the Pythagorean theorem, correlation, and regression, then moves into hands-on instruction with industry tools such as Excel, SQL, R, Python, and Power BI. Along the way, readers learn how to explore data, evaluate performance, and make informed decisions across team operations, player valuation, and sport business strategy. The book features real-world examples, chapter exercises, and review questions designed to reinforce key concepts through application. A dedicated section on data visualization walks readers through designing reports and dashboards using Power BI and Tableau. It also introduces the growing role of artificial intelligence in sport, showing how tools like machine learning and coding assistants can enhance analysis. A robust ancillary program also provides support to students with additional practice opportunities. With its practical focus and clear structure, An Introduction to Applied Sport Analytics is ideal for undergraduate and graduate courses in sport management, analytics, and business, as well as for professionals seeking to build essential skills in a data-driven sport industry.

  • Mathematical Statistics with Applications in R

    • 4th Edition
    • Kandethody M. Ramachandran + 1 more
    • English
    Mathematical Statistics with Applications in R, Fourth Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications that spans numerous foundational and essential concepts in the field. The book covers many modern statistical computational and simulation concepts, including Exploratory Data Analysis, the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. The final chapter of the book provides a step-by-step approach to modelling, analysis, and interpretation data from real-world applications, from the environment and cyber security to health and finance. By combining discussion on the theory of statistics with a wealth of engaging, real-world applications, this book helps students approach statistical problem-solving in a logical manner with accessible, step-by-step procedures on relatable topics. Computational aspects are covered through R and SAS examples.

  • Introductory Statistics

    • 5th Edition
    • Sheldon M. Ross
    • English
    Introductory Statistics, Fifth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods.Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that they are really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples.Application... and examples refer to real-world issues, such as gun control, stock price models, vaccines and other health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others.

  • Essential Statistics, Regression, and Econometrics

    • 3rd Edition
    • Gary Smith
    • English
    Essential Statistics, Regression, and Econometrics, Third Edition will helps students in introductory statistics courses develop statistical reasoning and critical thinking skills. The book demonstrates the power, elegance, and beauty of statistical reasoning, providing hundreds of new and updated examples and discussing the uses and potential abuses of statistics. Examples are drawn from real, contemporary areas to showcase that statistical reasoning is not an irrelevant abstraction, but instead an important part of everyday life. This updated resource highlights recent, exciting discoveries and provides a thorough foundation for students, instructors, and researchers alike, all of which are approaching the field from different backgrounds.Innovati... in its extended emphasis on statistical reasoning, real data, pitfalls in statistical analysis, the perils of p-hacking and data mining, and modeling issues, including functional forms and causality, the book includes extensive word problems that emphasize intuition, understanding, and practical applications.

  • Implementing R for Statistics

    • 1st Edition
    • Muhammad Imran + 3 more
    • English
    Implementing R for Statistics provides comprehensive coverage of basic statistical concepts using this important open-source programming language tool, from installing R and RStudio, to exploring its basic structure and uses, to extending some core functions such as vectors, basic mathematical operations, and data frames. The book will help readers understand the latest advances in the R programming language, as R allows for sophisticated and elegant data visualization. Illustrated examples are an integral part of the text, carefully designed to apply the core principles illustrated in the text to emerging topics in the field.The text also focuses on exploiting the flexible and user-friendly nature of R. Basic concepts and recent advances in the field, including understanding the R basics, as well as implementing and practicing them in statistics, are also covered. This first edition is an essential text for students, lecturers, data scientists, and applied researchers in all areas of statistics, as well as in related fields such as biostatistics, health care, finance, risk management, social sciences, market research, and environmental and climate research.

  • Handbook of Statistical Analysis

    AI and ML Applications
    • 3rd Edition
    • Robert Nisbet + 2 more
    • English
    Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers, and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business problems, weigh the strengths and weaknesses of modern data analysis algorithms, and employ the right analytical methods for practical application. This resource is an ideal guide for users who want to address massive and complex datasets with many standard analytical approaches and be able to evaluate analyses and solutions objectively. It includes clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques; offers accessible tutorials; and discusses their application to real-world problems.

  • An Introduction to Probability and Statistical Inference

    • 3rd Edition
    • George G. Roussas
    • English
    An Introduction to Probability and Statistical Inference, Third Edition guides the reader through probability models and statistical methods to develop critical-thinking skills. Written by award-winning author George Roussas, this valuable text introduces a thinking process to help users obtain the best solution to a posed question or situation and provides a plethora of examples and exercises to illustrate applying statistical methods to different situations.

  • An Introductory Handbook of Bayesian Thinking

    • 1st Edition
    • Stephen C. Loftus
    • English
    An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for students with some background in calculus and introductory statistics, particularly for nonstatisticians with a sufficient mathematical background, the text provides a gentle introduction to Bayesian ideas with a wide array of supporting examples from a variety of fields.

  • Probability and Statistics for Physical Sciences

    • 2nd Edition
    • Brian Martin + 1 more
    • English
    Probability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical sciences. This brief yet systematic introduction explains the origin of key techniques, providing mathematical background and useful formulas. The text does not assume any background in statistics and is appropriate for a wide-variety of readers, from first-year undergraduate students to working scientists across many disciplines.

  • Introduction to Probability Models

    • 13th Edition
    • Sheldon M. Ross
    • English
    *Textbook and Academic Authors Association (TAA) McGuffey Longevity Award Winner, 2024*A trusted market leader for four decades, Sheldon Ross’s Introduction to Probability Models offers a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Through its hallmark exercises and real examples, this valuable course textIntroduction to Probability Models provides the reader with a comprehensive course in the subject, from foundations to advanced topics.