Probability and statistics

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL).

Here is a book for clinicians, clinical investigators, trainees, and graduates who wish to develop their proficiency in the planning, execution, and interpretation of clinical and epidemiological research.

Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests.

Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights.

Mixing up various disciplines frequently produces something that are profound and far-reaching.

This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs.

This book is designed as a textbook for graduate students and as a resource for researchers seeking a thorough mathematical treatment of its subject.

Powerful analytical tools from statistical physics, guided by field observations are applied to spread of epidemics and movement ecology.

This book deals with the basics of parameter estimation and state estimation as the fundamental building blocks of mathematical modelling activity in the broader field of control theory.

This volume presents a selection of research papers on various topics at the interface of statistics and computer science.

Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics.

This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking.

Die vorliegende Einführung in die Stochastik, die sich vorwiegend an Studierende der Informatik richtet, geht in ihrer Konzeption im wesentlichen von den folgenden drei Gesichtspunkten aus: 1.

This book provides an introduction to operational research methods and their application in the agrifood and environmental sectors.

In the signal-processing research community, a great deal of progress in higher-order statistics (HOS) began in the mid-1980s.

Josef Anton Strini analyzes a special stochastic optimal control problem.

Thistimely text presents a comprehensive guide to genetic association, a new andrapidly expanding field that aims to elucidate how our genetic code (genotypes)influences the traits we possess (phenotypes).

Stochastic differential equations play an increasingly important role in modeling the dynamics of a large variety of systems in the natural sciences, and in technological applications.

This book is a comprehensive introduction to financial modeling that teaches advanced undergraduate and graduate students in finance and economics how to use R to analyze financial data and implement financial models.

Techniques for interpreting commonly used discrete choice models, illustrated with extensive examples including replication code and data.

This volume constitutes the papers of the 3rd International Workshop on Active Inference, IWAI 2022, held in Grenoble, France, in conjunction with ECML/PKDD, on September 19, 2022.

Physically Unclonable Functions (PUFs) translate unavoidable variations in certain parameters of materials, waves, or devices into random and unique signals.

Models in Statistical Social Research provides a comprehensive insight of models used in statistical social research based on statistical data and methods.

This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017.

Operation Research methods are often used in every field of modern life like industry, economy and medicine.

Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model.

Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials.

The emphasis of the book is on the question of Why - only if why an algorithm is successful is understood, can it be properly applied, and the results trusted.

This book serves as a practical guide to methods and statistics in medical research.

This book comprises the proceedings of the 4th International Conference on Computational Engineering (ICCE 2017), held in Darmstadt, Germany on September 28-29, 2017.

Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior.

This coherent guide equips applied statisticians to make good choices and proper interpretations in real investigations facing real data.

Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data.

This book describes various ways of approaching and interpreting the data produced by clinical trial studies, with a special emphasis on the essential role that biostatistics plays in clinical trials.

There has been a lot of innovation in systems engineering and some fundamental advances in the fields of optics, imaging, lasers, and photonics that warrant attention.

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori.

This book introduces undergraduate students of engineering and science to applied mathematics essential to the study of many problems.

A compact introduction to this active and powerful area of research, combining basic theory, core techniques, and recent applications.

A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by using animated graphics of the data.

Dieses praxisbezogene Lehrbuch zeigt anhand vieler Beispiele die Nutzung von Microsoft Excel und VBA in unterschiedlichen Feldern der Stochastik.

The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers.

This book presents the theory and methods of flexible and generalized uncertainty optimization.

This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems.

This book delves into the complexities of fault estimation and fault-tolerant control for nonlinear time-delayed systems.

Developed from the authors' longstanding course on decision and risk analysis, Value-Added Decision Making for Managers explores the important interaction between decisions and management action and clarifies the barriers to rational decision making.

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