Spatial Data Analysis

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Mult

Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates m

The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies.Today, the volume, velocity, and variety of data are increasing rapid

Describes the principles and methods of data analysis in an approach that can be understood by readers without specific knowledge of statistics or programming This book teaches readers without sp

Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis, design, integration, monitoring, and derivatives.This book is about data

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will descr

All scientific disciplines prize predictive success. Conventional statistical analyses, however, treat prediction as secondary, instead focusing on modeling and hence estimation, testing, and detailed physical interpretation, tackling these tasks before the predictive adequacy of a model is established. This book outlines a fully predictive approach to statistical problems based on studying predictors; the approach does not require predictors correspond to a model although this important special case is included in the general approach. Throughout, the point is to examine predictive performance before considering conventional inference. These ideas are traced through five traditional subfields of statistics, helping readers to refocus and adopt a directly predictive outlook. The book also considers prediction via contemporary 'black box' techniques and emerging data types and methodologies where conventional modeling is so difficult that good prediction is the main criterion available

This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of

Don't let a fear of numbers hold you back.Today's business environment brings with it an onslaught of data, but leaving the analysis to others in your company just won't cut it. Now more than ever, ma

Kaplan's LSAT PrepTests 52-61 Unlocked features comprehensive explanations for every question in the LSAC's official 10 New Actual, Official LSAT PrepTests with Comparative Reading. Reviewing

For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.

Egocentric network analysis is used widely across the social sciences, especially in anthropology, political science, economics, and sociology, and is increasingly being employed in communications, informatics, and business and marketing studies. Egocentric network analysis requires a unique set of data collection and analysis skills that overlap only minimally with other network methodologies. However, until now there has been no single reference for conceptualizing, collecting, and analyzing egocentric social network data. This comprehensive guide to study design, data collection, and analysis brings together the state of knowledge with the most effective research tools to guide newcomers to this field. It is illustrated with many engaging examples and graphics and assumes no prior knowledge. Covering the entire research process in a logical sequence, from conceptualizing research questions to interpreting findings, this volume provides a solid foundation for researchers at any stage

Egocentric network analysis is used widely across the social sciences, especially in anthropology, political science, economics, and sociology, and is increasingly being employed in communications, informatics, and business and marketing studies. Egocentric network analysis requires a unique set of data collection and analysis skills that overlap only minimally with other network methodologies. However, until now there has been no single reference for conceptualizing, collecting, and analyzing egocentric social network data. This comprehensive guide to study design, data collection, and analysis brings together the state of knowledge with the most effective research tools to guide newcomers to this field. It is illustrated with many engaging examples and graphics and assumes no prior knowledge. Covering the entire research process in a logical sequence, from conceptualizing research questions to interpreting findings, this volume provides a solid foundation for researchers at any stage

Foreword by Steven PinkerBlending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast

How we understand and define qualitative data is changing, with implications not only for the techniques of data analysis, but also how data are collected. New devices, technologies and online spaces

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data.

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data.

This book is published open access under a CC BY 4.0 license.It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cl

Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose whether highly fluctuating and random appearing data are most likel

This book is an update of the competitiveness rankings for Greater China economies at the sub-national and regional level with the latest available data. The study uses a comprehensive methodology whi

Use Excel 2016’s statistical tools to transform your data into knowledge Conrad Carlberg shows how to use Excel 2016 to perform core statistical tasks every business professional, student,

This unique text/reference presents an overview of the computational aspects of protein crystallization, describing how to build robotic high-throughput and crystallization analysis systems. The cover

"This book addresses the challenges associated with data analysis through providing guidance in data retrieval and analysis and examples of high-quality research making use of these data sets. It incl

This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines su

Now in paperback format, this is the first work to examine data privacy laws across Asia, covering all 26 countries and separate jurisdictions, and with in-depth analysis of the 14 which have speciali

Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinfo

In this volume, expert practitioners present a compilation of methods of functional data analysis (often referred to as “systems biology”) and its applications in drug discovery, medicine, and basic d

Cybermetric Techniques to Evaluate Organizations Using Web-Based Data proposes a complete and multifaceted analysis model, integrating quantitative and qualitative measures (extracted from web usabili

Introduce your students to programming with C++ using today's definitive choice for teaching a first programming language course -- C++ PROGRAMMING: FROM PROBLEM ANALYSIS TO PROGRAM DESIGN, 8E. D.S. M

Introducing a revolutionary new model for the statistical analysis of experimental data In this important book, internationally acclaimed statistician, Chihiro Hirotsu, goes beyond classical ana

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Dela

This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

This book is intended as a guide to the analysis and presentation of experimental results. It develops various techniques for the numerical processing of experimental data, using basic statistical met

This book highlights selected current data and its relevance in the human health care system, offering a fundamental primer on genetics and human health.With the advent of new high-throughput technolo

This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores

Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information no

Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information no

This book constitutes the refereed proceedings of the 13th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2017, held in Ustron, Poland, in May/June 2017. It con