Probability & Statistics

This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors p...

Developed over 20 years of teaching academic courses, the Handbook of Financial Risk Management can be divided into two main parts: risk management...

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revol...

Since the publication of the by now classical Johnson and Kotz Continuous Multivariate Distributions (Wiley, 1972) there have been substantial deve...

This book present graphical methods for analysing data. Some methods are new and some are old, some require a computer and others only paper and pe...

This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: sta...

Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks a...

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult ...

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to stu...

The implementation problem lies at the heart of a theory of institutions. Simply stated, the aim of implementation theory is to investigate in a ri...

Originally published in 1923 Chance and Error examines the vagaries of chance, and how this is the result of the interference of yes and no. The bo...

As computers proliferate and as the field of computer graphics matures, it has become increasingly important for computer scientists to understand ...

Create Top-Quality Figures Using SAS Producing High-Quality Figures Using SAS/GRAPH and ODS Graphics Procedures gives statisticians and SAS program...

Categorical data-comprising counts of individuals, objects, or entities in different categories-emerge frequently from many areas of study, includi...

Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with t...

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world...

Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have e...

Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to...

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is...

The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of ...

Using R for Modelling and Quantitative Methods in Fisheries has evolved and been adapted from an earlier book by the same author and provides a det...

People tend to rank values of all kinds linearly from good to bad, but there is little reason to think that this is reasonable or correct. This boo...

A core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to nois...

Do you want to use R to tell stories? This book was written for youwhether you already know some R or have never coded before.Most R texts focus on...