Probability & Statistics

All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to...

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is...

____________________What is AIQ? How does it work? Most importantly, how can it help us? Two leading data scientists offer an up-close and user-friendly look at artificial intelligence and how to harness its power for a better world. 'A positive and...

A lucid presentation of statistical physics and thermodynamics which develops from the general principles to give a large number of applications of the theory.Reviews"Stimulating reading" --New ScientistBook InformationISBN 9780750633727Author L D...

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and...

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized...

Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental...

This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are...

An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of...

Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780985867003Author Larry HatcherFormat PaperbackPage Count 646Imprint Shadow Finch Media LLCPublisher Shadow Finch Media LLCWeight(grams)...

The term Financial Derivative is a very broad term which has come to mean any financial transaction whose value depends on the underlying value of the asset concerned. Sophisticated statistical modelling of derivatives enables practitioners in the...

Have you been told you need to do multilevel modeling, but you can't get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense? Help is here! This book unpacks these statistical...

An Introduction to Quantum Stochastic Calculus aims to deepen our understanding of the dynamics of systems subject to the laws of chance both from the classical and the quantum points of view and stimulate further research in their unification. This is...

Stata Tips provides concise and insightful notes about commands, features, and tricks that will help you obtain a deeper understanding of Stata.The book comprises the contributions of the Stata community that have appeared in the Stata Journal since 2003...

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...

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today. You'll start by learning basic concepts of recommender...

Provides new insights into the accuracy and value of online panels for completing surveys Over the last decade, there has been a major global shift in survey and market research towards data collection, using samples selected from online panels. Yet...

A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the...

This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and engineering. In finance, the stochastic calculus is applied to pricing options by no arbitrage. In biology, it is...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780993367939Author Dr James V StoneFormat PaperbackPage Count 188Imprint Sebtel PressPublisher Sebtel PressWeight(grams) 259g

Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall...

This classic textbook offers a clear exposition of modern probability theory and of the interplay between the properties of metric spaces and probability measures. The first half of the book gives an exposition of real analysis: basic set theory, general...

The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic,...

Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied...

This book provides a comprehensive introduction to the theory of stochastic calculus and some of its applications. It is the only textbook on the subject to include more than two hundred exercises with complete solutions.After explaining the basic...

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with...

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780593297063Author Vaclav SmilFormat HardbackPage Count 336Imprint VikingPublisher Penguin Putnam IncWeight(grams) 539gDimensions(mm) 236mm * 162mm * 29mm

Use this practical guide to the Splunk operational data intelligence platform to search, visualize, and analyze petabyte-scale, unstructured machine data. Get to the heart of the platform and use the Search Processing Language (SPL) tool to query the...

Now available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are...

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using...

"Overall, this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference. Each chapter provides an R implementation of the introduced causal concepts and models and concludes...

This book provides a visual and intuitive coverage of the core theory of linear models. Designed to develop fluency with the underlying mathematics and to build a deep understanding of the principles, it's an excellent basis for a one-semester course on...

A complete guide to the theory and practical applications of probability theory An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781912477722Author Malcom BennettFormat HardbackPage Count 250Imprint Eyewear PublishingPublisher Eyewear PublishingWeight(grams) 859gDimensions(mm) 255mm *...

During the past half-century, exponential families have attained a position at the center of parametric statistical inference. Theoretical advances have been matched, and more than matched, in the world of applications, where logistic regression by...

Learn how to get better answers in map analysis when you use spatial measurements and statistics. Spatial measurements and statistics give you a powerful way to analyze geospatial data, but you don't need to understand complex mathematical theories to...

Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide...

This edition contains a large number of additions and corrections scattered throughout the text, including the incorporation of a new chapter on state-space models. The companion diskette for the IBM PC has expanded into the software package ITSM: An...