Probability and statistics

Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies.

Hereditary systems (or systems with either delay or after-effects) are widely used to model processes in physics, mechanics, control, economics and biology.

The present monograph develops a versatile and profound mathematical perspective of the Wright--Fisher model of population genetics.

Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error.

This book presents an easy-to-use tool for time series analysis and allows the user to concentrate upon studying time series properties rather than upon how to calculate the necessary estimates.

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering.

ACM Monograph Series: A Computational Logic focuses on the use of induction in proving theorems, including the use of lemmas and axioms, free variables, equalities, and generalization.

This book provides a general framework for learning sparse graphical models with conditional independence tests.

This textbook provides the foundation for a course that takes PhD students in empirical accounting research from the very basics of statistics, data analysis, and causal inference up to the point at which they conduct their own research.

This monograph looks at causal nets from a philosophical point of view.

The articles in this book represent the major contributions at the NATO Advanced Research Workshop that was held from 6 to 9 July 1987 in the magnificent setting of Dyffryn House and Gardens, in St.

A clear and simple introduction to geostatistics, demystifying complex concepts and making formulas and statistical tests easy to apply.

This book reconsiders statistical methods from the point of view of entropy, and introduces entropy-based approaches for data analysis.

Advanced R helps you understand how R works at a fundamental level.

This 3-volume reference covers the entire field of epidemiology, from statistical methods and study design, to specialized areas such as molecular epidemiology, and applications in clinical medicine and health services research.

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition presents fundamental, classical statistical concepts at the doctorate level.

This book presents a collection of selected papers that represent the current variety of research on the teaching and learning of probability.

This book collects select chapters on modern industrial problems related to uncertainties and vagueness in the expert domain of knowledge.

Mixed modelling is very useful, and easier than you think!

In recent years, many pharmaceutical companies and clinical research organizations have been focusing on the development of traditional Chinese (herbal) medicines (TCMs) as alternatives to treating critical or life-threatening diseases and as pathways to personalized medicine.

The goal of the 2019 conference on Stochastic Processes and Algebraic Structures held in SPAS2019, Vasteras, Sweden, from September 30th to October 2nd 2019, was to showcase the frontiers of research in several important areas of mathematics, mathematical statistics, and its applications.

Readers who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text.

Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment.

Pseudolinear Functions and Optimization is the first book to focus exclusively on pseudolinear functions, a class of generalized convex functions.

AP Teachers' #1 Choice!

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics.

If you know how to program with Python and also know a little about probability, youre ready to tackle Bayesian statistics.

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis.

This book constitutes the referred proceedings of the 11th International Workshop on Practical Applications of Stochastic Modelling, PASM 2022, was held in Alicante, Spain, in September 2022.

This unique book presents a learn-by-doing introduction to geostatistics.

Managing Airline Networks: Design, Integration and Innovative Technologies is a fully comprehensive description of state-of-the-art network management practices at airlines.

To curb the impacts of rising CO2 emissions, the Intergovernmental Panel on Climate Change report states that a net zero target needs to be achieved by the year 2055.

Learning a computer language like R can be either frustrating, fun or boring.

There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience.

Praise for the First Edition: "e;For a beginner [this book] is a treasure trove; for an experienced person it can provide new ideas on how better to pursue the subject of applied statistics.

This book contains eleven articles which provide empirical applications as well as theoretical extensions of some of the most exciting recent developments in time-series econometrics.

This 2002 book is a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean.

Risk assessment theory and practice for graduate engineering students, practising engineers, designers and project managers, first published in 2005.

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars.

The primary objective of this book is to advance the state of the art in specifying and ?

This book offers essential, systematic information on the assessment of the spatial association between two processes from a statistical standpoint.

Benjamin Säfken entwickelt in seiner Arbeit fortgeschrittene statistische Verfahren, wie semiparametrische Regressionsmodelle, für kleinräumige Fallzahlprognosen für die Versorgungsplanung.

Introduction to Nuclear Engineering serves as an accompanying study guide for a complete, introductory single-semester course in nuclear engineering.

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems.

This publication provides guidance on preparing data to be input into an international computerised database for clinical case histories of persons accidentally exposed to whole body irradiation.