Mathematical and statistical software Books

This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management...

R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are...

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival...

The creation, accumulation, and use of copious amounts of data are driving rapid change across a wide variety of industries and academic disciplines. This ‘Big Data’ phenomenon is the result of...

Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts...

Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software. It is...

Algebraic Operads: An Algorithmic Companion presents a systematic treatment of Gröbner bases in several contexts. The book builds up to the theory of Gröbner bases for operads due to the second...

Learning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming...

Introduction to Political Analysis in R is a comprehensive guide for students and researchers eager to delve into the intersection of data science, statistics, and political science. Aimed at...

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are...

Unlike the first edition, the new edition has been split into two books.Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling...

Unlike the first edition, the new edition has been split into two books.Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling...

An understanding and working knowledge of the basic principles of statistics are of central importance in understanding the sport and health sciences. Introduction to Statistics in Human Performance:...

Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and...

Multilevel and Longitudinal Modeling with IBM SPSS, Third Edition, demonstrates how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Versions 25-27. Annotated...

An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling brings the power of modern Bayesian thinking,...

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as...

Future microwave, wireless communication systems, computer chip designs, and sensor systems will require miniature fabrication processes in the order of nanometers or less as well as the fusion of...

Future microwave, wireless communication systems, computer chip designs, and sensor systems will require miniature fabrication processes in the order of nanometers or less as well as the fusion of...

Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the...

The book examines the profound historical roots and expansive potential of computation and artificial intelligence. Bridging ancient mathematical traditions—like India’s Sulva Sutras and the ideas of...

The linear model and its extensions play fundamental roles in both theoretical and applied statistics, due to their transparency and interpretability in modeling empirical data. This textbook, based...

The linear model and its extensions play fundamental roles in both theoretical and applied statistics, due to their transparency and interpretability in modeling empirical data. This textbook, based...

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences. Enrolling in their first statistics course, students are often apprehensive or...

Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control...

This book is an overview of the Bayesian approach to applying the most important inferential methods of statistical science. It is designed as a textbook for advanced undergraduate and master’s...

This book is an overview of the Bayesian approach to applying the most important inferential methods of statistical science. It is designed as a textbook for advanced undergraduate and master’s...

This book explores how deep learning enhances statistical methods for hypothesis testing, point estimation, optimization, interpretation, and other aspects. It uniquely demonstrates leveraging deep...

This book explores how deep learning enhances statistical methods for hypothesis testing, point estimation, optimization, interpretation, and other aspects. It uniquely demonstrates leveraging deep...

This book provides a comprehensive and practical guide to fitting complex Bayesian survival, longitudinal and joint models using the Integrated Nested Laplace Approximations (INLA) methodology, a...

This book introduces modern methods for estimating and analysing factorial experiments, including a new Hadamard matrix-based technique for 2n designs. It covers confounded, asymmetrical, and...

This book is an introduction to Python for intermediate learners. It allows readers to take a slow and steady approach to building upon their understanding of Python code. While there are many books,...

This book is an introduction to Python for intermediate learners. It allows readers to take a slow and steady approach to building upon their understanding of Python code. While there are many books,...

This book is intended to equip the reader with concept knowledge on multilinear regression methods, and develop technical skills while solving problems with the R programming language. The goal is...

In the five previous editions of Advanced Engineering Mathematics with MATLAB®, the author presented a text firmly grounded in mathematics that engineers and scientists must understand and know how...

This text is designed to update the Differential Geometry course by making it more relevant to today’s students. This new approach emphasizes applications and computer programs aimed at...

Since the publication of the second edition of Richard Plant’s bestselling textbook Spatial Data Analysis in Ecology and Agriculture Using R, the methodology of spatial data analysis and the suite of...

This book presents a practical approach for researchers seeking to analyse patient data over time. It serves as a comprehensive guide, utilising the R programming language to analyse complex datasets...

This book provides a comprehensive exploration of generalization in deep learning, focusing on both theoretical foundations and practical strategies. It delves deeply into how machine learning...

This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB®-based exercises to help readers effectively...

This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB®-based exercises to help readers effectively...

Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control...

Mathematical Foundations of Artificial Intelligence: Basics of Manifold Theory is the first volume in a two‑part series. Together, they establish a unifying mathematical framework based on smooth...

Data clustering, an interdisciplinary field with diverse applications, has gained increasing popularity since its origins in the 1950s. Over the past six decades, researchers from various fields have...

Exploratory and Robust Data Analysis: A Modern Applied Statistics Guide Using SPSS and R is an essential resource for students, researchers, and professionals seeking a comprehensive yet practical...

This text is designed to update the Differential Geometry course by making it more relevant to today’s students. This new approach emphasizes applications and computer programs aimed at...

Since the publication of the second edition of Richard Plant’s bestselling textbook Spatial Data Analysis in Ecology and Agriculture Using R, the methodology of spatial data analysis and the suite of...

Recognizing the vast potential in analyzing big data through machine learning (ML) and artificial intelligence (AI) technologies, companies are acknowledging these technologies as essential for...