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Spatio–Temporal Methods in Environmental Epidemiology with R
Spatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, explores the interface between environmental epidemiology and spatio-temporal modeling. It links recent developments in spatio-temporal theory with epidemiological applications. Drawing on real-life problems, it shows how recent advances in methodology can assess the health risks associated with environmental hazards. The book's clear guidelines enable the implementation of the methodology and estimation of risks in practice. New additions to the Second Edition include: a thorough exploration of the underlying concepts behind knowledge discovery through data; a new chapter on extracting information from dat...
Spatio-Temporal Methods in Environmental Epidemiology
Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and
Oxford Handbook of Epidemiology for Clinicians
The Oxford Handbook of Epidemiology for Clinicians provides all the information required by students and junior doctors who need to understand and translate key epidemiological concepts into medical practice. Unlike standard textbooks in this area, the focus throughout is on clinical applications of epidemiological knowledge. Divided into four sections, the handbook begins with the basics of epidemiology in the clinic, moving on to the theories behind evidence-based practice, discussions of optimum methods and studies, and then ends by looking at the epidemiology of common diseases. The material is presented in a logical manner, from problems to the most appropriate solutions or tools to be applied. Interesting topics such as controversies in prevention intervention encourage discussion and thought, and the authors pose sensible and important questions throughout. This handbook is a must for all junior doctors, medical students, and clinicians who need to apply epidemiological concepts to day-to-day practice or who want a practical step-by-step guide to undertaking research, conducting reviews of evidence, or writing up publications.
Statistical Inference
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 statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone wit...
Data and Society
Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.
The Little Green Data Book 2016
The Little Green Data Book 2016 is a pocket-sized ready reference on key environmental data for over 200 countries. Key indicators are organized under the headings of agriculture, forestry, biodiversity, oceans, energy, emission and pollution, and water and sanitation. For the third year, The Little Green Data Book presents a new set of ocean-related indicators, highlighting the role of oceans in economic development.
Generalized Linear Mixed Models
Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling, this book helps them see the big picture – linear modeling as broadly understood and its intimate connection with statistical design and mathematical statistics. For readers experienced in statistical practice, but new to GLMMs, the book provides a comprehensive introduction to GLMM methodology and its underlying theory. Unlike textbooks that focus on classical linear models or generalized linear models or mixed models, t...
Rethinking Wilderness and the Wild
Rethinking Wilderness and the Wild: Conflict, Conservation and Co-existence examines the complexities surrounding the concept of wilderness. Contemporary wilderness scholarship has tended to fall into two categories: the so-called ‘fortress conservation’ and ‘co-existence’ schools of thought. This book, contending that this polarisation has led to a silencing and concealment of alternative perspectives and lines of enquiry, extends beyond these confines and in particular steers away from the dilemmas of paradise or paradox in order to advance an intellectual and policy agenda of plurality and diversity rather than of prescription and definition. Drawing on case studies from Australia...
A Course in the Large Sample Theory of Statistical Inference
Provides accessible introduction to large sample theory with moving alternatives Elucidates mathematical concepts using simple practical examples Includes problem sets and solutions for each chapter Uses the moving alternative formulation developed by LeCam but requires a minimum of mathematical prerequisites
R for Business Analytics
R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. T...
