Probability & Statistics

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. Th...

Researchers often do not analyze nonreplicated experiments statistically because they are unfamiliar with existing statistical methods that may be ...

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory fro...

Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC complian...

In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere mor...

This book focuses on the application of the partial hedging approach from modern math finance to equity-linked life insurance contracts. It provide...

Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such a...

Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on pa...

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behav...

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of paramete...

Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory an...

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stoc...

In clinical trial practice, controversial statistical issues inevitably occur regardless of the compliance with good statistical practice and good ...

Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in ...

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applicati...

Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality. An effective way to mitigate this proble...

Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introd...

In an easy-to-understand, nontechnical yet mathematically elegant manner, An Introduction to Exotic Option Pricing shows how to price exotic option...

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 geog...

While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always h...

Unexpected Expectations: The Curiosities of a Mathematical Crystal Ball explores how paradoxical challenges involving mathematical expectation ofte...