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Books in Statistics and probability

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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
      Implementing R for Statistics is a timely first edition textbook that provides comprehensive coverage of basic statistical concepts using R, an important open-source programming language tool. This book guides the readers through understanding the R basics, from installing R and RStudio to exploring its basic structure and uses, to implementing and practicing these in statistics. Using the sophisticated and elegant data visualization of R, this book explains the latest advances in the R programming language using illustrated examples carefully designed to apply the core principles discussed in the text to emerging topics in the field. It also provides useful insights into the process of developing R packages and creating metadata, focusing on exploiting the flexible and user-friendly nature of R. Written by an international and experienced team of authors, Implementing R for Statistics is an essential text for students, lecturers, data scientists, and applied researchers in all areas of statistics and related fields such as biostatistics, health care, finance, risk management, social sciences, market research, and environmental and climate research.

    • An Introduction to Stochastic Modeling

      • 5th Edition
      • September 17, 2025
      • Gabriel Lord + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 1 5 5 2 7
      • eBook
        9 7 8 0 4 4 3 3 1 5 5 3 4
      An Introduction to Stochastic Modeling, Fifth Edition bridges the gap between basic probability and an intermediate level course in stochastic processes, serving as the foundation for either a one-semester or two-semester course in stochastic processes for students familiar with elementary probability theory and calculus. The objectives are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide an integrated treatment of theory, applications and practical implementation. A well-regarded resource for many years, the text is an ideal foundation for a broad range of students.

    • Statistics in Industry and Government

      • 1st Edition
      • Volume 53
      • August 6, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 3 1 4 2 2 3
      • eBook
        9 7 8 0 4 4 3 3 1 4 2 3 0
      Statistics in Industry and Government covers industrial quality control and high-class quality maintenance in products. The book aims to cover as many applications that use statistics as an underlying tool in bringing the best quality products and industrial designs. Chapters in this new release include Analysis of Official Time Series with Ecce Signum, an R Package for Multivariate Signal Extraction and Forecasting, The Maturity Structure of Public Debt: A Granular Approach Using Indian Data, Harnessing the power of spherical intersection: A less arbitrary unsupervised learning method applied to pattern recognition within financial data, and much more.Other chapters in this release include The Use of Causal Inference with Structural Models in Industry, MSME Statistics in India, The Importance of Accurate, Timely, Credible Crime Data to Inform Crime and Justice Policy, Combining Information from Multiple Sources in Official Statistics, Active Learning of Computer Experiment with both Quantitative and Qualitative Inputs, On the use of machine learning methods for missing data problems, Optimal Experimental Planning for Experiments Based on Coherent Systems with Industrial Applications, and more.

    • Stochastic Theory of Service Systems

      • 1st Edition
      • May 23, 2025
      • L. Kosten
      • I. N. Sneddon + 1 more
      • English
      • Paperback
        9 7 8 1 4 8 3 1 1 8 1 6 1
      • eBook
        9 7 8 1 4 8 3 1 5 0 5 8 1
      International Series of Monographs in Pure and Applied Mathematics, Volume 103: Stochastic Theory of Service Systems focuses on the principles, methodologies, and approaches involved in the stochastic theory of service systems. The publication first examines the general description of service systems, characteristics of the arrival process, standard cases, and the distribution of waiting-times in the system M/M/c-delay. Discussions focus on "random" condition, probability of delay and average waiting-time for the system M/M/c-delay, Engset formula, and probability of blocking for the system M/M/c-blocking. The text then examines general holding-time assumption, non-stationary behavior, and priority. Topics include pre-emptive priority, transient behavior of the system M/G/1-delay, Markov process with a finite number of states, and hyperexponential distributions. The manuscript takes a look at simulation, arrival and service in batches, and restricted availability, including approximate determination of probabilities of blocking, "unscheduled ferry problem", principles of roulette simulation, and implementation of randomness. The publication is a dependable source material for researchers interested in the stochastic theory of service systems.

    • Markov Chains: Theory and Applications

      • 1st Edition
      • Volume 52
      • April 15, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 2 9 5 7 6 8
      • eBook
        9 7 8 0 4 4 3 2 9 5 7 7 5
      Markov Chains: Theory and Applications, Volume 52 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on topics such as Markov Chain Estimation, Approximation, and Aggregation for Average Reward Markov Decision Processes and Reinforcement Learning, Ladder processes: symmetric functions and semigroups, Continuous-time Markov Chains and Models: Study via Forward Kolmogorov System, Analysis of Data Following Finite-State Continuous-Time Markov Chains, Computational applications of poverty measurement through Markov model for income classes, and more.Other sections cover Estimation and calibration of continuous time Markov chains, Additive High-Order Markov Chains, The role of the random-product technique in the theory of Markov chains on a countable state space., On estimation problems based on type I Longla copulas, and Long time behavior of continuous time Markov chains.

    • Probability Models

      • 1st Edition
      • Volume 51
      • September 27, 2024
      • English
      • Hardback
        9 7 8 0 4 4 3 2 9 3 2 8 3
      • eBook
        9 7 8 0 4 4 3 2 9 3 2 9 0
      Probability Models, Volume 51 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on Stein’s methods, Probabilities and thermodynamics third law, Random Matrix Theory, General tools for understanding fluctuations of random variables, An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions, Probability Models Applied to Reliability and Availability Engineering, Backward stochastic differential equation– Stochastic optimization theory and viscous solution of HJB equation, and much more.Additional chapters cover Probability Models in Machine Learning, The recursive stochastic algorithm, randomized urn models and response-adaptive randomization in clinical trials, Random matrix theory: local laws and applications, KOO methods and their high-dimensional consistencies in some multivariate models, Fourteen Lectures on Inference for Stochastic Processes, and A multivariate cumulative damage model and some applications.

    • 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.

    • 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.

    • 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.

    • Modeling and Analysis of Longitudinal Data

      • 1st Edition
      • Volume 50
      • February 7, 2024
      • English
      • Hardback
        9 7 8 0 4 4 3 1 3 6 5 1 1
      • eBook
        9 7 8 0 4 4 3 1 3 6 5 2 8
      Longitudinal Data Analysis, Volume 50 in the Handbook of Statistics series covers how data consists of a series of repeated observations of the same subjects over an extended time frame and is thus useful for measuring change. Such studies and the data arise in a variety of fields, such as health sciences, genomic studies, experimental physics, sociology, sports and student enrollment in universities. For example, in health studies, intra-subject correlation of responses must be accounted for, covariates vary with time, and bias can arise if patients drop out of the study.

Related subjects

Probability theory and stochastic processes

Statistics