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ANOVA and Mixed Models
ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs...
Escape Routes: Contemporary Perspectives on Life After Punishment
Escape Routes: Contemporary Perspectives on Life After Punishment addresses the reasons why people stop offending, and the processes by which they are rehabilitated or resettled back into the community. Engaging with, and building upon, renewed criminological interest in this area, Escape Routes nevertheless broadens and enlivens the current debate. First, its scope goes beyond a narrowly-defined notion of crime and includes, for example, essays on religious redemption, the lives of ex-war criminals, and the relationship between ethnicity and desistance from crime. Second, contributors to this volume draw upon a number of areas of contemporary research, including urban studies, philosophy, h...
Islamic Law in Past and Present
Islamic Law in Past and Present, written by the lawyer and Islamicist Mathias Rohe, is the first comprehensive study for decades on Islamic law, legal theory, reform mechanisms and the application of Islamic law in Islamic countries and the Muslim diaspora. It provides information based on an abundance of Oriental and Western sources regarding family and inheritance law, contract and economic law, penal law, constitutional, administrative and international law. The present situation and ‘law in action’ are highlighted particularly. This includes examples collected during field studies on the application of Islamic law in India, Canada and Germany.
Tidy Finance with R
This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the tidyverse family of R packages. We then provide the code to prepare common open source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, p...
Medicine, Faith and Politics in Agogo
Medicine, Faith and Politics in Agogo examines the development of health care delivery at a former mission hospital in Ghana. It reveals the configurations of interests, values, and ideologies that shaped the development and implementation of health care practices, strategies, and concepts. By providing an in-depth analysis, the book contributes a particular perspective on the history of health care delivery in rural Africa and beyond. It addresses topics that are still heavily under-researched. These include the 'decolonisation' of health care as well as the development and implementation of medical concepts for 'developing countries' such as primary health care. Dissertation. (Series: Swiss African Studies / Schweizerische Afrikastudien / Etudes africaines suisses, Vol. 13) [Subject: African Studies, History, Religious Studies, Health Care Studies, Sociology]
Spatial Analysis in Geology Using R
The integration of geology with data science disciplines, such as spatial statistics, remote sensing, and geographic information systems (GIS), has given rise to a shift in many natural sciences schools, pushing the boundaries of knowledge and enabling new discoveries in geological processes and earth systems. Spatial analysis of geological data can be used to identify patterns and trends in data, to map spatial relationships, and to model spatial processes. R is a consolidated and yet growing statistical programming language with increasing value in spatial analysis often replacing, with advantage, GIS tools. By providing a comprehensive guide for geologists to harness the power of spatial ...
Modern Data Visualization with R
Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights. It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects plots, correlation plots, biplots, and the mapping of geographic data. Both static and interactive graphics are described and the use of color, shape, shading, grouping, annotation, and animations are covered in detail. The book moves from a default look and feel for graphs, to graphs with customized colors, fonts, legends, annotations, and organiz...
Winning with Data Science
Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams. Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrat...
Spatial Data Science
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, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries. In the second part of the book, these concepts are illustrated with data science examples using the R language. In the third part, statistical modelling approaches are demonstrated using real world data examples. After reading this book, the reader will be well equipped to avoid a number of major spatial data analy...
Model-Based Clustering, Classification, and Density Estimation Using mclust in R
Model-Based Clustering, Classification, and Denisty Estimation Using mclust in R Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate clustering or classification method to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models. Key features of the b...
