Probability & Statistics

This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics. Generalized linear models (GLMs) are ...

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models,...

Financial Econometrics Using Stata is an essential reference for graduate students, researchers, and practitioners who use Stata to perform intermediate or advanced methods. After discussing the characteristics of financial time series, the authors...

Statistics and Health Care Fraud: How to Save Billions helps the public to become more informed citizens through discussions of real world health care examples and fraud assessment applications. The author presents statistical and analytical methods used...

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their...

Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between...

Probability and Measure Theory, Second Edition, is a text for a graduate-level course in probability that includes essential background topics in analysis. It provides extensive coverage of conditional probability and expectation, strong laws of large...

This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most...

How do you predict something that has never happened before? There's a useful calculation being employed by Wall Street, Silicon Valley and maths professors all over the world, and it predicts that the human species will become extinct in 760 years...

This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such...

This motivating textbook gives a friendly, rigorous introduction to fundamental concepts in equilibrium statistical mechanics, covering a selection of specific models, including the Curie-Weiss and Ising models, the Gaussian free field, O(n) models, and...

An insightful, hands-on focus on the statistical methods used by compensation and human resources professionals in their everyday work Across various industries, compensation professionals work to organize and analyze aspects of employment that deal...

In this fascinating book, mathematician Ed Beltrami takes a close enough look at randomness to make it mysteriously disappear. The results of coin tosses, it turns out, are determined from the start, and only our incomplete knowledge makes them look...

Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated...

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well...

Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear...

Expanded and revised to include new computing exercises using actual data along with tips, solutions and a set of updated questions. Computer use is encouraged to facilitate analysis of data sets too large to be done by hand; to assist in the drawing of...

Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in...

This low-priced write-in workbook offers extensive practice, mostly context-free, for students to gain confidence in statistics at Level 3.Book InformationISBN 9781446903315Author Peter SherranFormat PaperbackPage Count 96Imprint Edexcel LimitedPublisher...

Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and...

bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility...

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing...

A clear easy-to-read guide to presenting your message using statistical data Poor presentation of data is everywhere; basic principles are forgotten or ignored. As a result, audiences are presented with confusing tables and charts that do not make...

Reinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective. The book is written for researchers with an interest in...

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections,...

* A self-contained introduction to probability, exchangeability and Bayes' rule provides a theoretical understanding of the applied material. * Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses...

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the...

This book is a comprehensive guide to multivariate probability for students who have an elementary knowledge of probability and are ready to move on to more advanced concepts Topics covered include: A review of basic probability theory, including core...

for SATB unaccompanied with optional congregation William Blake's poem, 'A Cradle Song', is brought to life in this elegant setting by Chilcott. The gentle, recurring melody is passed from sopranos to altos, supported by 'oo's and 'ah's in the lower...

New England theologian Jonathan Edwards came to prominence at the culmination of a dramatic paradigm shift in millennialism that had begun in the sixteenth century, declaring that a thousand-year earthly kingdom would arrive in the future. For Edwards,...

Cancer is a major healthcare burden across the world and impacts not only the people diagnosed with various cancers but also their families, carers, and healthcare systems. With advances in the diagnosis and treatment, more people are diagnosed early and...

APPLIED REGRESSION ANALYSIS applies regression to real data and examples while employing commercial statistical and spreadsheet software. Covering the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and...

"[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."-Frederic Schick, Journal of PhilosophyBook InformationISBN 9780226395821Author Richard C...

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probability laws, central and non-central limit theorems for...

This book provides a general introduction to the R Commander graphical user interface (GUI) to R for readers who are unfamiliar with R. It is suitable for use as a supplementary text in a basic or intermediate-level statistics course. It is not intended...

We may learn from our mistakes, but this work argues that, where experimental knowledge is concerned, we haven't begun to learn enough. It provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own...

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of...

Heavy tails -extreme events or values more common than expected -emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising,...

For one- or two-semester courses in Introductory Statistics. Statistically significant Introductory Statistics MyLab Revision, 10th Edition, Global Edition is ideal for introductory statistics classes that emphasize statistical reasoning and critical...

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R...