Spatial Data Analysis

This book provides a collection of concepts, algorithms, and techniques that effectively harness the power of Spatial Network Big Data. Reading this book is a first step towards understanding the imme

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation an

Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications teaches everyday biological data analysis to the undergraduate and graduate levels. Through numerous examples and over 100

This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analy

Agent-Based Spatial Simulation with NetLogo, Volume 2: Advanced Concepts provides a flexible and intuitive approach that connects both data and theories, making it ideal for the majority of scientific

Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern quantitative tools and techniques designed specifically to meet t

As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in

The description for this book, Data Analysis for Scientists and Engineers, will be forthcoming.

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univaria

This book highlights the extraordinary range of areas to which geographical analysis and spatial modelling can bring lessons and insights. It shows how these techniques have been used to address ‘real

This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John

This volume covers a large area, from the description of methodologies for data analysis to the real application. Chapters focus on methodologies for preprocessing of microarray data, a survey of miRN

This book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- quality metrics to be created using arbitrary features. This

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area.It demonstrates that Big Data Analysis opens up

A practical guide to data mining using SQL and ExcelData Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to per

This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience. The only prerequisite is a first-year statistics course and familiarity with a computing package such as R, Stata, SPSS, or SAS. Though the book is not tied to a particular computing language, its figures and analyses were all created using R. Relevant R code, data sets, and links to public data sets are available from www.cambridge.org/97811071130

Learn to use powerful Python libraries for effective data processing and analysisAbout This BookLearn the basic processing steps in data analysis and how to use Python in this area through supported p

Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and stor

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and func

The Art and Science of Analyzing Software Data: Analysis Patterns provides valuable information on the analysis methods that often transfer between projects, not only the algorithms derived from data

This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s stru

Data Envelopment Analysis (DEA) is often overlooked in empirical work such as diagnostic tests to determine whether the data conform with technology which, in turn, is important in identifying technic

See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which g

Doing Sociolinguistics: A practical guide to data collection and analysis provides an accessible introduction and guide to the methods of data collection and analysis in the field of sociolinguistics.

Doing Sociolinguistics: A practical guide to data collection and analysis provides an accessible introduction and guide to the methods of data collection and analysis in the field of sociolinguistics.

Providing a practical, hands-on introduction to data conceptualization, measurement and association, this book gives students step-by-step instruction on data analysis using the latest version of SPSS

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent yearsThis book covers kernel analysis topics ranging from the fundamental theo

Functional data is data in the form of curves that is becoming a popular method for interpreting scientific data. Statistical Analysis of Functional Data provides an authoritative account of function

This volume gives a thorough and comprehensive analysis of the Kurdish issue in Turkey from a spatial perspective that takes into account geographical variations in identity formation, exclusion and p

This book provides an introduction to incorporating preference information in Data Envelopment Analysis (DEA) with a special emphasis in Value Efficiency Analysis. In addition to theoretical considera

This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natura

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resou

Go beyond design concepts—build dynamic data visualizations using JavaScriptJavaScript and jQuery for Data Analysis and Visualization goes beyond design concepts to show readers how to build dynamic,

Michael Batty Centre for Advanced Spatial Analysis, University College London Landscapes, like cities, cut across disciplines and professions. This makes it especially difficult to provide an overall

Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport per

Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport per

The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well

This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability th

How does knowledge of the body in space relate to an understanding of space itself? Spatial cognition is discussed from two closely related perspectives: the internal mapping of external stimuli (e.g., landmarks and sensory perception of environmental information) and the internal mapping of internally perceived stimuli (e.g., kinesthetic and visual imagery), and their subsequent effects on behaviour. Clarification of what spatial information is present in most perceptual processes and how this is used cognitively in relation to the self in space is then established. Major points and controversies of the various models are discussed, along with evolutionary perspectives of spatial perception and object recognition and comparisons between human and non-human spatial cognitive abilities and behaviours. Written for postgraduate students and researchers, the authors present theoretical and experimental accounts at multiple levels of analysis - perceptual, behavioural and cognitive - provid