Probability and statistics

Using real-life examples from the banking and insurance industries, Quantitative Operational Risk Models details how internal data can be improved based on external information of various kinds.

Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology.

Actuarial Models: The Mathematics of Insurance, Second Edition thoroughly covers the basic models of insurance processes.

Drawing on the authors' varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences.

Using an accessible, nontechnical approach, the third edition of Regression Basics introduces readers to the fundamentals of statistical regression.

This book is a concise hands-on guide that provides students a useful tool for a systematic approach to scientific inquiry.

This book provides sample exercises, techniques, and solutions to employ mathematical modeling to solve problems in Operations Research and Business Analytics.

 This book is an updated edition of Modeling Binary Correlated Responses Using SAS, SPSS and R, and now it includes the use of STATA.

 This book is an updated edition of Modeling Binary Correlated Responses Using SAS, SPSS and R, and now it includes the use of STATA.

Statistical Analysis: The Basics provides an engaging and easy to read primer on this sometimes daunting subject.

This book covers topics in 2 parts: 1) Review of FDA Guidance, 2) Novel Designs and Analyses.

This book covers topics in 2 parts: 1) Review of FDA Guidance, 2) Novel Designs and Analyses.

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies.

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners.

Expert Guidance on the Math Needed for 3D Game ProgrammingDeveloped from the authors' popular Game Developers Conference (GDC) tutorial, Essential Mathematics for Games and Interactive Applications, Third Edition illustrates the importance of mathematics in 3D programming.

This book covers contemporary topics in mathematical analysis and its applications and relevance in other areas of research.

Set-Indexed Martingales offers a unique, comprehensive development of a general theory of Martingales indexed by a family of sets.

This book presents the theory of rational decisions involving the selection of stopping times in observed discrete-time stochastic processes, both by single and multiple decision-makers.

Understand Up-to-Date Statistical Techniques for Financial and Actuarial ApplicationsSince the first edition was published, statistical techniques, such as reliability measurement, simulation, regression, and Markov chain modeling, have become more prominent in the financial and actuarial industries.

Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data.

Introduction to Financial Mathematics is ideal for an introductory undergraduate course.

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts.

Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA).

A team of ASQ Fellows has created this study guide with new questions predominantly based on the best-selling third edition of The Certified Six Sigma Green Belt Handbook.

Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples.

The book is a collection of different aspects of outliers and related topics written by experts.

Competitive Innovation and Improvement: Statistical Design and Control explains how to combine two widely known statistical methods'statistical design and statistical control in a manner that can solve any business, government, or research problem quickly with sustained results.

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures.

This book describes some approaches for developing the numerical models to efficiently predict the formation of extreme waves which can pose a threat to the safety of marine structures.

This book describes some approaches for developing the numerical models to efficiently predict the formation of extreme waves which can pose a threat to the safety of marine structures.

Keine ausführliche Beschreibung für "Mathematische Theorie der Zuverlässigkeit" verfügbar.

The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest.

Actuarial loss models are statistical models used by insurance companies to estimate the frequency and severity of future losses, set premiums, and reserve funds to cover potential claims.

As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences.

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

Interpreting poll data as a prediction of election outcomes is a practice as old as the field, rooted in a fundamental misunderstanding of what poll data means.

Designed for a one-semester course, Applied Statistics for Business and Economics offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world.

This book provides a concise overview of a variety of techniques for analyzing statistical, scientific, and financial data, using MATLAB(R) to integrate several approaches to data analysis and statistics.

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist.

Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility?

This book presents statistics and data science methods for risk analytics in quantitative finance and insurance.

This peerless reference/text unfurls a unified and systematic study of the two types of mathematical models of dynamic processes-stochastic and deterministic-as placed in the context of systems of stochastic differential equations.