Mathematical and statistical software

This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level.

This book was written to provide guidance for those who need to apply statistical methods for practical use.

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available.

This textbook offers an essential introduction to survey research and quantitative methods.

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data.

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and  astrophysics in the past twenty years.

This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R.

This book was written to provide guidance for those who need to apply statistical methods for practical use.

Courses on linear algebra and numerical analysis need each other.

Courses on linear algebra and numerical analysis need each other.

This book develops the time series univariate models through the Econometric Modeler tool.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R.

This book is a self-guided tour of MATLAB for engineers and life scientists.

This book teaches readers to integrate data analysis techniques into humanities research practices using the R programming language.

In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development.

Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking.

This book helps the reader make use of the mathematical models of biological phenomena starting from the basics of programming and computer simulation.

Companies are scrambling to integrate AI into their systems and operations.

Companies are scrambling to integrate AI into their systems and operations.

This textbook provides a compact but comprehensive treatment that guides students through applied numerical analysis, using MATLAB(R)/Simulink(R).

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with the applications of Excel VBA, Python and R.

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences.

This book provides frequently studied and used machines together with soft computing methods such as evolutionary computation.

Application of Numerical Methods in Engineering Problems Using MATLAB(R) presents an analysis of structures using numerical methods and mathematical modeling.

Application of Numerical Methods in Engineering Problems Using MATLAB(R) presents an analysis of structures using numerical methods and mathematical modeling.

The 49Th Scientific meeting of the Italian Statistical Society was held in June 2018 in Palermo, with more than 450 attendants.

Advance your skills in building predictive models with SAS!

This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-25 June 2021.

This book provides a reference for people working in the design, development, and manufacturing of medical devices.

Advance your skills in building predictive models with SAS!

Challenge your brain with math!

Challenge your brain with math!

This book presents a unified and up-to-date introduction to ROC methodologies, covering both diagnosis (classification) and prediction.

This book presents a unified and up-to-date introduction to ROC methodologies, covering both diagnosis (classification) and prediction.

This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language.

This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language.

R is open source statistical computing software.

Master the Statistical Techniques for Six Sigma Operations, While Boosting Your Excel and Minitab Skills!

Tough Test Questions?

This book focuses on statistical inferences related to various combinatorial stochastic processes.

Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniquesKey Features[] Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages[] Understand how to apply useful data analysis techniques in R for real-world applications[] An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysisBook DescriptionThis cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently.

A practical, professional guide to MATLAB computational techniques and engineering applicationsMATLAB Numerical Methods with Chemical Engineering Applications shows you, step by step, how to use MATLAB to model and simulate physical problems in the chemical engineering realm.

This book is about the role and potential of using digital technology in designing teaching and learning tasks in the mathematics classroom.

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields.

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences.