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Books in Statistics

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    • Implementing R for Statistics

      • 1st Edition
      • January 19, 2026
      • Muhammad Imran + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 8 3 2 1 2
      • eBook
        9 7 8 0 4 4 3 3 8 3 2 2 9
      Written by an international and experienced team of authors, Implementing R for Statistics is a textbook designed for students of statistics and mathematics courses and professional statisticians. This timely first edition 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. It helps 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 covered in Implementing R for Statistics. The book also provides useful insights into the process of developing R packages. The text includes new content on applied statistics and R implementation, as well as updated material on building an R package and creating metadata. 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.

    • An Introductory Handbook of Bayesian Thinking

      • 1st Edition
      • April 17, 2024
      • Stephen C. Loftus
      • English
      • Paperback
        9 7 8 0 3 2 3 9 5 4 5 9 4
      • eBook
        9 7 8 0 4 4 3 2 9 1 1 1 1
      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.

    • An Introduction to Probability and Statistical Inference

      • 3rd Edition
      • May 16, 2024
      • George G. Roussas
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 7 2 0 9
      • eBook
        9 7 8 0 4 4 3 1 8 7 2 1 6
      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.

    • Handbook of Statistical Analysis

      • 3rd Edition
      • September 16, 2024
      • Robert Nisbet + 2 more
      • English
      • Hardback
        9 7 8 0 4 4 3 1 3 2 7 3 5
      • Paperback
        9 7 8 0 4 4 3 1 5 8 4 5 2
      • eBook
        9 7 8 0 4 4 3 1 5 8 4 6 9
      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.

    • Probability and Statistics for Physical Sciences

      • 2nd Edition
      • September 5, 2023
      • Brian Martin + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 9 6 9 2
      • eBook
        9 7 8 0 4 4 3 1 8 9 7 0 8
      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.

    • Hybrid Censoring Know-How

      • 1st Edition
      • January 6, 2023
      • Narayanaswamy Balakrishnan + 2 more
      • English
      • Hardback
        9 7 8 0 1 2 3 9 8 3 8 7 9
      • eBook
        9 7 8 0 1 2 3 9 8 3 9 0 9
      Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers will find information on the significance of censored data in theoretical and applied contexts, and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography.

    • Introduction to Probability Models

      • 13th Edition
      • June 30, 2023
      • Sheldon M. Ross
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 7 6 1 2
      • eBook
        9 7 8 0 4 4 3 1 8 7 6 0 5
      *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.

    • Simulation

      • 6th Edition
      • June 14, 2022
      • Sheldon M. Ross
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 7 3 9 0
      • eBook
        9 7 8 0 3 2 3 8 9 9 6 1 1
      Simulation, Sixth Edition continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers will learn to apply the results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions. By explaining how a computer can be used to generate random numbers and how to use these random numbers to generate the behavior of a stochastic model over time, this book presents the statistics needed to analyze simulated data and validate simulation models.

    • Basic Statistics with R

      • 1st Edition
      • February 20, 2021
      • Stephen C. Loftus
      • English
      • Paperback
        9 7 8 0 1 2 8 2 0 7 8 8 8
      • eBook
        9 7 8 0 1 2 8 2 0 9 2 6 4
      Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines.

    • Statistical Methods

      • 4th Edition
      • April 16, 2021
      • Donna L. Mohr + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 0 4 3 5
      • eBook
        9 7 8 0 3 2 3 8 9 9 8 8 8
      Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.