Books in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

Books Journals

11-20 of 3351 results in All results

Process Data Analytics

1st Edition
September 1, 2027
Biao Huang + 1 more
English

Process Data Analytics is an accessible undergraduate text on data science for engineers, crafted as a helpful study tool for the growing field of courses specially tailored to these subjects. The text aims to serve as the core book for fundamental courses in data science or machine learning and illustrates the various machine learning methods with process engineering applications. The book also contains advanced content, such as probabilistic models, suitable for use by postgraduate students and researchers. Split into four main parts, the authors first provide the mathematical foundations of regression, discussing the different types of data that students and practitioners may encounter in the process industry, as well as different data preprocessing and visualization techniques. Then, the book discusses various conventional statistical methods and eventually moves on to introduce some of the common machine-learning methods for regression. The final section covers the design of experiments, leading students with case studies and lessons with real-world applications. Process Data Analytics seeks to support readers in the field across several related disciplines, from Engineering to Mathematics courses. From covering basic lessons on subjects such as linear algebra and optimization to delving deeper into model representation of simple, multiple, non-linear, and Bayesian regression, the text ensures that students have a solid understanding of concepts before moving to more adventurous and advanced topics. The book has a unique concentration on dealing with the process data, as well as delves into regression methods. This valuable first edition delivers engaging explanations and illustrative examples while discussing the role and importance of data science in modern studies of the field.

Applications of Piecewise Defined Fractional Operators

1st Edition
December 1, 2026
Abdon Atangana + 1 more
English

Applications of Piecewise Defined Fractional Operators, Volume Two introduces new mathematical methods to derive complex modeling solutions with stability, consistency, and convergence. These tools include new types of non-local derivatives and integrals, such as fractal-fractional derivatives and integrals. Drs. Atangana and Araz present the theoretical and numerical analyses of newly introduced piecewise differential and integral operators where crossover behaviors are observed, along with applications. The book contains foundational concepts that will help readers better understand piecewise differential and integral calculus and their applications to modeling processes. Concepts are applied to heat transfer, groundwater transport, groundwater flow, telegraph dynamics, heart rhythm, and others. Applying principles introduced in the first volume, new numerical schemes are introduced to derive numerical solutions to these new equations, and the stability, consistency, and convergence analysis of these new numerical approaches are presented.

Epidemiological Modeling with Application to Covid-19

1st Edition
December 1, 2026
Abdon Atangana + 1 more
English

Epidemiological Modeling with Application to Covid-19 presents information about statistical, numerical, stability, and theoretical analyses for nine different Covid-19 models. Those models are considered with classical and fractional derivatives, which is a generalization of the classical analysis. The authors present their newly introduced rate indicator function for the prediction of the waves of Covid-19 spread. Moreover, future prediction of Covid-19 spread is presented for some countries. The authors also provide a new approach to modeling epidemiological issues in general, which has been tested against the spread of COVID-19 in several nations.This book provides in-depth analysis of the spread of Covid-19, including discussion of theoretical and numerical results, including a novel modeling method called strength numbers that was created under the umbrella of acceleration, which provides a determiner of the power of disease spread. These significant characteristics might be the key to understanding and anticipating the spread of infections and diseases more generally.

Doing Bayesian Data Analysis

3rd Edition
October 1, 2026
English

Doing Bayesian Data Analysis: A Tutorial with R, Stan, brms, and the tidyverse , Third Edition, provides a carefully scaffolded tutorial from beginning concepts to advanced, realistic data analyses. The book uses a proven sequence of topics unique to Doing Bayesian Data Analysis. The first part covers foundational concepts of statistical models, probability, Bayesian reasoning, and computer programming in R and the tidyverse. The second part introduces all the concepts and methods of Bayesian data analysis, including the Stan modeling language, by using the simplest possible data structures and statistical models. The third part covers the generalized linear model, including multilevel (a.k.a. hierarchical) versions of regression and analysis of variance, for a variety of data types (metric, ordinal, nominal, dichotomous, count), using the convenient computer package called brms. Every concept and case is illustrated with detailed examples, and all computer code is available at the book’s website. This book is intended for self-learners or classroom learning, for first-year graduate students, advanced undergraduates, and professionals. The methods apply to any field, including social sciences, biological sciences, and physical sciences, for any setting, including academia, government, business, and industry.

Implementing R for Statistics

1st Edition
September 1, 2026
Muhammad Imran + 3 more
English

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.

Real Analysis

1st Edition
April 1, 2026
Rudi Weikard + 2 more
English

"Real Analysis: Examples, Concepts, and Applications" instructs in core proofs, theorems, and approaches of real analysis, as illustrated via compelling exercises and carefully crafted, practical examples. From chapter one onward, students are asked to apply concepts to reinforce understanding and gain applied experience in real analysis. In particular, exercises challenge students to use key proofs of major real analysis theorems to encourage independent thinking and problem solving, and new areas of research powered by real analysis are introduced. Following early chapters on core concepts and approaches of real analysis, the authors apply real analysis across integration on product spaces, radon functionals, bounded variation and lebesgue-stieltjes measures, convolutions, probability, and differential equations, among other topics. Advanced exercises are also included at the end of each chapter, with exercise difficulty level noted for instructors, and solutions included in an appendix.

Quantitative Biology

1st Edition
March 1, 2026
Padmanabhan Seshaiyer + 1 more
English

Quantitative Biology introduces and implements quantitative and data-driven approaches for analyzing biological and bio-inspired systems, covering the foundations of mathematical modeling, analysis, and computation. The book presents a practical mix of both theory and computation for a variety of biological applications, with tied-in, engaging project activities, instruction, programming language, and technological tools. Modeling approaches in the book combine mathematical foundations, statistical reasoning, and computational thinking, with application in compartmental, agent-based, bio image, biological interaction, and neural network modeling, as well as machine learning, parameter identification, and more, with a later chapter considering applications across societal challenges. Each chapter includes exposure to models and modeling, a foundational instructional framework, benchmark applications, and numerical simulations with a literate programming guided style, helping readers go beyond replication models and into prediction and data-driven discovery. A companion website also features interactive code to accompany projects across each chapter.

Quaternionic Generalized Inverses

1st Edition
March 1, 2026
Ivan Kyrchei
English

Quaternionic Generalized Inverses introduces and applies the theory of row-column determinants for the study of quaternion matrices, and thus empowers student and faculty research across wider areas of matrix theory, real, and complex analysis. Here, quaternion linear algebra is considered alongside core aspects of matrix theory, including the construction of an inverse matrix and Cramer's rule for constructing quaternion systems of linear equations, the core inverse, the core-EP inverse, and various composite inverses. Similarly, main frameworks of generalized inverse theory, such as the Moore-Penrose and Drazin inverse, are introduced and demonstrated across exercises in text. Inter-related concepts of differential equations, discrete analogies, advanced calculus modeling, and approximation theory highlight wider areas of applications. Problems, solutions, and chapter conclusions across the book further reinforce learning and application, and recommendations for course integration help faculty incorporate chapter material in their teaching.

Eleventh Hour CISSP®

4th Edition
January 1, 2026
Eric Conrad + 2 more
English

Eleventh Hour CISSP®: Study Guide, Fourth Edition provides a study guide keyed directly to the most current version of the CISSP exam. This streamlined book includes only core certification information, making it ideal for last-minute studying. The main objectives of the exam are covered concisely, with key concepts highlighted. The CISSP certification is the most prestigious, globally-recognized, vendor neutral exam for information security professionals. Over 100,000 professionals are certified worldwide with many more joining their ranks. All eight domains are covered completely and concisely, giving readers the best possible chance of acing the exam.This new edition is aligned to cover all of the material in the most current version of the exam’s Common Body of Knowledge.

Boundary Value Problems and Partial Differential Equations

7th Edition
January 1, 2026
Jonathan Mitchell + 3 more
English

For over fifty years, Boundary Value Problems and Partial Differential Equations has provided advanced students an accessible and practical introduction to deriving, solving, and interpreting explicit solutions involving partial differential equations with boundary and initial conditions. Fully revised and now in its Seventh Edition, this valued text aims to be comprehensive without affecting the accessibility and convenience of the original. The resource’s main tool is Fourier analysis, but the work covers other techniques, including Laplace transform, Fourier transform, numerical methods, characteristics, and separation of variables, as well, to provide well-rounded coverage. Mathematical modeling techniques are illustrated in derivations, which are widely used in engineering and science. In particular, this includes the modeling of heat distribution, a vibrating string or beam under various boundary conditions and constraints. New to this edition, the text also now uniquely discusses the beam equation. Throughout the text, examples and exercises have been included, pulled from the literature based on popular problems from engineering and science. These include some "outside-the-box" exercises at the end of each chapter, which provide challenging and thought-provoking practice that can also be used to promote classroom discussion. Chapters also include Projects, problems that synthesize or dig more deeply into the material that are slightly more involved than standard book exercises, and which are intended to support team solutions. Additional materials, exercises, animations, and more are also accessible to students via links and in-text QR codes to support practice and subject mastery.