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Handbook of Survival Analysis

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field the handbook focuses on advances in survival analysis techniques covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

GBP 66.99

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Discrete Mathematics with Ducks

Discrete Mathematics with Ducks Second Edition is a gentle introduction for students who find the proofs and abstractions of mathematics challenging. At the same time it provides stimulating material that instructors can use for more advanced students. The first edition was widely well received with its whimsical writing style and numerous exercises and materials that engaged students at all levels. The new expanded edition continues to facilitate effective and active learning. It is designed to help students learn about discrete mathematics through problem-based activities. These are created to inspire students to understand mathematics by actively practicing and doing which helps students better retain what they’ve learned. As such each chapter contains a mixture of discovery-based activities projects expository text in-class exercises and homework problems. The author’s lively and friendly writing style is appealing to both instructors and students alike and encourages readers to learn. The book’s light-hearted approach to the subject is a guiding principle and helps students learn mathematical abstraction. Features:The book’s Try This! sections encourage students to construct components of discussed concepts theorems and proofsProvided sets of discovery problems and illustrative examples reinforce learningBonus sections can be used by instructors as part of their regular curriculum for projects or for further study

GBP 38.99

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Elementary Number Theory

Elementary Number Theory Gove Effinger Gary L. Mullen This text is intended to be used as an undergraduate introduction to the theory of numbers. The authors have been immersed in this area of mathematics for many years and hope that this text will inspire students (and instructors) to study understand and come to love this truly beautiful subject. Each chapter after an introduction develops a new topic clearly broken out in sections which include theoretical material together with numerous examples each worked out in considerable detail. At the end of each chapter after a summary of the topic there are a number of solved problems also worked out in detail followed by a set of supplementary problems. These latter problems give students a chance to test their own understanding of the material; solutions to some but not all of them complete the chapter. The first eight chapters discuss some standard material in elementary number theory. The remaining chapters discuss topics which might be considered a bit more advanced. The text closes with a chapter on Open Problems in Number Theory. Students (and of course instructors) are strongly encouraged to study this chapter carefully and fully realize that not all mathematical issues and problems have been resolved! There is still much to be learned and many questions to be answered in mathematics in general and in number theory in particular.

GBP 48.99

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Urban Informatics Using Big Data to Understand and Serve Communities

Urban Informatics: Using Big Data to Understand and Serve Communities introduces the reader to the tools of data management analysis and manipulation using R statistical software. Designed for undergraduate and above level courses this book is an ideal onramp for the study of urban informatics and how to translate novel data sets into new insights and practical tools. The book follows a unique pedagogical approach developed by the author to enable students to build skills by pursuing projects that inspire and motivate them. Each chapter has an Exploratory Data Assignment that prompts readers to practice their new skills on a data set of their choice. These assignments guide readers through the process of becoming familiar with the contents of a novel data set and communicating meaningful insights from the data to others. Key Features: The technical curriculum consists of both data management and analytics including both as needed to become acquainted with and reveal the content of a new data set. Content that is contextualized in real-world applications relevant to community concerns. Unit-level assignments that educators might use as midterms or otherwise. These include Community Experience assignments that prompt students to evaluate the assumptions they have made about their data against real world information. All data sets are publicly available through the Boston Data Portal. | Urban Informatics Using Big Data to Understand and Serve Communities

GBP 48.99

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Math and Art An Introduction to Visual Mathematics

Math and Art: An Introduction to Visual Mathematics explores the potential of mathematics to generate visually appealing objects and reveals some of the beauty of mathematics. It includes numerous illustrations computer-generated graphics photographs and art reproductions to demonstrate how mathematics can inspire or generate art. Focusing on accessible visually interesting and mathematically relevant topics the text unifies mathematics subjects through their visual and conceptual beauty. Sequentially organized according to mathematical maturity level each chapter covers a cross section of mathematics from fundamental Euclidean geometry tilings and fractals to hyperbolic geometry platonic solids and topology. For art students the book stresses an understanding of the mathematical background of relatively complicated yet intriguing visual objects. For science students it presents various elegant mathematical theories and notions. Features Provides an accessible introduction to mathematics in art Supports the narrative with a self-contained mathematical theory with complete proofs of the main results (including the classification theorem for similarities) Presents hundreds of figures illustrations computer-generated graphics designs photographs and art reproductions mainly presented in full color Includes 21 projects and approximately 280 exercises about half of which are fully solved Covers Euclidean geometry golden section Fibonacci numbers symmetries tilings similarities fractals cellular automata inversion hyperbolic geometry perspective drawing Platonic and Archimedean solids and topology New to the Second Edition New exercises projects and artworks Revised reorganized and expanded chapters More use of color throughout | Math and Art An Introduction to Visual Mathematics

GBP 56.99

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Demand Forecasting for Executives and Professionals

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting. It discusses how individuals and firms should think about forecasting and guidelines for good practices. It introduces readers to the subject of time series presents basic and advanced forecasting models from exponential smoothing across ARIMA to modern Machine Learning methods and examines human judgment's role in interpreting numbers and identifying forecasting errors and how it should be integrated into organizations. This is a great book to start learning about forecasting if you are new to the area or have some preliminary exposure to forecasting. Whether you are a practitioner either in a role managing a forecasting team or at operationally involved in demand planning a software designer a student or an academic teaching business analytics operational research or operations management courses the book can inspire you to rethink demand forecasting. No prior knowledge of higher mathematics statistics operations research or forecasting is assumed in this book. It is designed to serve as a first introduction to the non-expert who needs to be familiar with the broad outlines of forecasting without specializing in it. This may include a manager overseeing a forecasting group or a student enrolled in an MBA program an executive education course or programs not specialising in analytics. Worked examples accompany the key formulae to show how they can be implemented. Key Features: While there are many books about forecasting technique very few are published targeting managers. This book fills that gap. It provides the right balance between explaining the importance of demand forecasting and providing enough information to allow a busy manager to read a book and learn something that can be directly used in practice. It provides key takeaways that will help managers to make difference in their companies. | Demand Forecasting for Executives and Professionals

GBP 44.99

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Large-Scale Machine Learning in the Earth Sciences

From the Foreword:While large-scale machine learning and data mining have greatly impacted a range of commercial applications their use in the field of Earth sciences is still in the early stages. This book edited by AshokSrivastava Ramakrishna Nemani and Karsten Steinhaeuser serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest…I hope that this book will inspire more computer scientists to focus on environmental applications and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences. Vipin Kumar University of MinnesotaLarge-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science computer science statistics and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources in the final chapter of the book.

GBP 44.99

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