Probability and statistics

This highly motivating introduction to statistical learning machines explains underlying principles in nontechnical language, using many examples and figures.

This book represents the porceedings of the 1989 Safety and Reliability Society Symposium held in Bath on the 11th and 12th of October on that topic.

Modern society depends heavily upon a host of systems of varying complexity to perform the services required.

Presenting the first definitive study of the subject, this Handbook of Biometric Anti-Spoofing reviews the state of the art in covert attacks against biometric systems and in deriving countermeasures to these attacks.

Large sample techniques are fundamental to all fields of statistics.

This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level.

Presents a unique study of Integrative Problem-Solving (IPS).

Algebraic statistics is a rapidly developing field, where ideas from statistics and algebra meet and stimulate new research directions.

A compact, highly-motivated introduction to some of the stochastic models found useful in the study of communications networks.

Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science.

Radio astronomy is irreversibly moving towards the exabyte era.

This book constitutes the refereed proceedings of the 10th International Conference on Information Theoretic Security, ICITS 2017, held in Hong Kong, China, in November/December 2017.

This book explains the advanced but essential concepts of Multivariate Statistics in a practical way while touching the mathematical logic in a befitting manner.

Hierarchy is a form of organisation of complex systems that rely on or produce a strong differentiation in capacity (power and size) between the parts of the system.

Statistische Verfahren werden in allen Naturwissenschaften, in der Wirtschaft, in der Technik und sogar zum Teil in den Geisteswissenschaften eingesetzt.

A modern introduction to statistics for undergraduates in physics, with worked examples and case studies to illustrate techniques presented.

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

This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021.

Throughout Don Benbow's extensive career, teaching mathematics and statistical courses to college students and corporate employees, one common question always popped up: how do you fix statistical errors in quality?

Linear Regression and its Application to Economics presents the economic applications of regression theory.

Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods.

Readers of this book will learn how to solve a wide range of optimal investment problems arising in finance and economics.

This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022.

Praise for the First Edition "e; [t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics.

An accessible introduction to performing meta-analysis across various areas of research The practice of meta-analysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion.

This Study Guide accompanies Statistics for Business and Financial Economics, 3rd Ed.

In recent years, many researchers in the psychology and statistical communities have paid increasing attention to test equating as issues of using multiple test forms have arisen and in response to criticisms of traditional testing techniques.

Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials.

The large and complex challenges the world is facing, the growing prevalence of huge data sets, and the new and developing ways for addressing them (artificial intelligence, data science, machine learning, etc.

An Introduction to Acceptance Sampling and SPC with R is an introduction to statistical methods used in monitoring, controlling and improving quality.

This book provides a novel perspective on human migration dynamics by examining it through the lenses of complex systems science and philosophy of science.

In recent years, mathematics has experienced amazing growth in the engineering sciences.

Data Analytics: A Small Data Approach is suitable for an introductory data analytics course to help students understand some main statistical learning models.

This book is an extension of the author's first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN).

The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector.

The First Book Dedicated to This Class of Longitudinal ModelsAlthough antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models.

The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies.

Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages.

Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities.

This book is devoted to the problems of construction and application of chi-squared goodness-of-fit tests for complete and censored data.

Self-contained and entertaining introduction to computational genomics, using a case-studies approach with Matlab demos.

This book concentrates on mining networks, a subfield within data science.

This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019.

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.

A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation.