General

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear...

Measurement is a fundamental concept that underpins almost every aspect of the modern world. It is central to the sciences, social sciences, medicine, and economics, but it affects everyday life. We measure everything - from the distance of far-off...

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear...

Exam board: Cambridge Assessment International EducationLevel: A-levelSubject: MathematicsFirst teaching: September 2018First exams: Summer 2020Endorsed by Cambridge Assessment International Education to provide full support for Paper 5 of the syllabus...

Apologies but we at Booksplease don't have a full description for this book.Reviews"Statistics are being used ever more widely in AI, climate studies, medicine and other areas. Yet they are hard to understand both mathematically and conceptually. Jun...

Linear Optimization and Dualiyy: A Modern Exposition departs from convention in significant ways. Standard linear programming textbooks present the material in the order in which it was discovered. Duality is treated as a difficult add-on after coverage...

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate...

Finance provides a dramatic example of the successful application of advanced mathematical techniques to the practical problem of pricing financial derivatives. This self-contained 2002 text is designed for first courses in financial calculus aimed at...

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which...

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic...

Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for...

Built specifically for statistical computing and graphics, the R language, along with its amazing collection of libraries and tools, is one of the most powerful tools you can use to tackle data analysis for business, research, and other data-intensive...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781607647621Author Sanjay MatangeFormat PaperbackPage Count 370Imprint SAS PublishingPublisher SAS PublishingWeight(grams) 636gDimensions(mm) 235mm * 191mm...

Statistical Analysis for the Reliability Engineering ProfessionalEffectively conduct reliability analysis using the world's leading statistical software. Reliability Analysis with Minitab (R) outlines statistical concepts and applications, explains the...

A daily glass of wine prolongs life-yet alcohol can cause life-threatening cancer. Some say raising the minimum wage will decrease inequality while others say it increases unemployment. Scientists once confidently claimed that hormone replacement therapy...

This introduction to random walks on infinite graphs gives particular emphasis to graphs with polynomial volume growth. It offers an overview of analytic methods, starting with the connection between random walks and electrical resistance, and then...

Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in...

This text is an accessible, student-friendly introduction to the wide range of mathematical and statistical tools needed by the forensic scientist in the analysis, interpretation and presentation of experimental measurements. From a basis of high school...

Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. This text offers easy access to this fundamental topic for many students of applied sciences at many levels. It includes...

This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology,...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9789738752016Author Catalin BarboianuFormat PaperbackPage Count 300Imprint InfaromPublisher InfaromWeight(grams) 405gDimensions(mm) 229mm * 152mm * 15mm

This established and popular text is regarded as one of the clearest and most comprehensive in its field. David Eadson has joined Jon Curwin and Roger Slater in the author team, and together they have sought to offer a more compact book with all the...

A brand new, fully updated edition of a popular classic on matrix differential calculus with applications in statistics and econometrics This exhaustive, self-contained book on matrix theory and matrix differential calculus provides a treatment of matrix...

Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care...

Applied Statistical Modelling for Ecologists provides a gentle introduction to the essential models of applied statistics: linear models, generalized linear models, mixed and hierarchical models. All models are fit with both a likelihood and a Bayesian...

Considering Poisson random measures as the driving sources for stochastic (partial) differential equations allows us to incorporate jumps and to model sudden, unexpected phenomena. By using such equations the present book introduces a new method for...

Elevate your machine learning skills using the Conformal Prediction framework for uncertainty quantification. Dive into unique strategies, overcome real-world challenges, and become confident and precise with forecasting. Key Features Master...

This book provides a hands-on guide to how financial models are actually implemented and used in practice, on a daily basis, for pricing and risk-management purposes. It shows how to put these models into use in production while minimizing the cost of...

This focuses on models and data that arise from repeated observations of a cross-section of individuals, households or companies. These models have found important applications within business, economics, education, political science and other social...

Social media has made charts, infographics and diagrams ubiquitous-and easier to share than ever. While such visualisations can better inform us, they can also deceive by displaying incomplete or inaccurate data, suggesting misleading patterns-or...

In this second book of what will be a four-volume series, the authors present, in a mathematically rigorous way, the essential foundations of both the theory and practice of algorithms, approximation, and optimization-essential topics in modern applied...

In the early seventeenth century, the outcome of something as simple as a dice roll was consigned to the realm of unknowable chance. Mathematicians largely agreed that it was impossible to predict the probability of an occurrence. Then, in 1654, Blaise...

This monograph aims to promote original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries. Such processes arise in numerous applications and are of interest in several areas of mathematical...

This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780805071344Author David SalsburgFormat PaperbackPage Count 352Imprint Holt PaperbackPublisher Henry Holt & Company IncWeight(grams) 334gDimensions(mm)...

With its emphasis on examples, exercises and calculations, this book suits advanced undergraduates as well as postgraduates and practitioners. It provides a clear treatment of the scope and limitations of mean-variance portfolio theory and introduces...

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...

The State of the Art in Transcriptome Analysis RNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical...

The 2nd edition of this successful book has several new features. The calibration discussion of the basic LIBOR market model has been enriched considerably, with an analysis of the impact of the swaptions interpolation technique and of the exogenous...

Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students. This accessible textbook provides an up-to-date introduction to the classical techniques and...