Multidimensional Data Visualization

Shows ordinary users how to tap the rich data analysis functionality of Excel, make sense of their organization's critical financial and statistical information, and put together compelling data prese

Information Generation is the story of the seminal role data plays in our lives and explains how the advance of our civilization has come hand in hand with our ability to collect and interpret data. S

This book replaces Intestinal Toxicology, one of the original books in the Target Organ series. It provides a complete, multidimensional overview of the entire gastrointestinal system involved in the

As one of the fastest growing technologies in our culture today, data communications and networking presents a unique challenge for instructors. As both the number and types of students are increasing

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concept

"Patient compliance is a multidimensional, multinational, and multidisease problem." So says a contributor who heads the Medical Science Institute, USA. Failure to take medicines in a prescribed manne

Businesses now rely almost entirely on applications and databases, causing data and storage needs to increase at astounding rates. It is therefore imperative for a company to optimize and simplify the

An indispensable resource to embodied spirituality reveals how to experience God rather than just engage God as an idea, sharing physical exercises, meditation practices, and visualization activities

This book is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as “market data?, the universe of content is ver

There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and sh

This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal backgro

Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data

Using network visualization and the study of the dynamics of marriage choices, Network Analysis and Ethnographic Problems expands the theory of social practice to show how changes in the structure of

Fathom Dynamic Data Software Version 2 is an easy-to-use software that bridges the gap between concrete and abstract mathematical and statistical concepts. This software lets students see and manipul

Social scientists have long relied on a wide range of tools to collect information about the social world, but as individual fields have become more specialised, researchers are trained to use a narrow range of the possible data collection methods. This book, first published in 2006, draws on a broad range of available social data collection methods to formulate a set of data collection approaches. The approaches described here are ideal for social science researchers who plan to collect new data about people, organisations, or social processes. Axinn and Pearce present methods designed to create a comprehensive empirical description of the subject being studied, with an emphasis on accumulating the information needed to understand what causes what with a minimum of error. In addition to providing methodological motivation and underlying principles, the book is filled with detailed instructions and concrete examples for those who wish to apply the methods to their research.

Social scientists have long relied on a wide range of tools to collect information about the social world, but as individual fields have become more specialised, researchers are trained to use a narrow range of the possible data collection methods. This book, first published in 2006, draws on a broad range of available social data collection methods to formulate a set of data collection approaches. The approaches described here are ideal for social science researchers who plan to collect new data about people, organisations, or social processes. Axinn and Pearce present methods designed to create a comprehensive empirical description of the subject being studied, with an emphasis on accumulating the information needed to understand what causes what with a minimum of error. In addition to providing methodological motivation and underlying principles, the book is filled with detailed instructions and concrete examples for those who wish to apply the methods to their research.

It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforceme

Despite mining's multidimensional role in the history of Utah since Euro-american settlement, there has never been a book that surveyed and contextualized its impact. From the Ground Up fill that gap

Dynamic data assimilation is the assessment, combination and synthesis of observational data, scientific laws and mathematical models to determine the state of a complex physical system, for instance as a preliminary step in making predictions about the system's behaviour. The topic has assumed increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. This book is designed to be a basic one-stop reference for graduate students and researchers. It is based on graduate courses taught over a decade to mathematicians, scientists, and engineers, and its modular structure accommodates the various audience requirements. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes

With accompanying software! Clinicians manage a lot of data - on assorted bits of paper and in their heads. This book is about better ways to manage and understand large amounts of clinical data. Fol

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This

A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by

Furnishing essential data on all areas of toxicity testing, this Second Edition provides guidance on the design and evaluation of product safety studies to help ensure regulatory acceptance.? Every ch

This book helps you make sense of the data your school district collects, including state student achievement results as well as other qualitative and quantitative data. Easy-to-use templates, tools,

In recent years, companies and government agencies have come to realize that the data they use represent a significant corporate resource, whose cost calls for management every bit as rigorous as the

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

In Coherence and Natural Language, Florian Wolf and Edward Gibson specify and evaluate criteria for descriptively adequate data structures for representing discourse coherence. They test the influence

Featuring sixty-seven illustrations, and providing an important reckoning and visualization of the previously hidden Jewish 'ghosts' within US art, Jewish Identities in American Feminist Art addresses

Introducing a revolutionary trend visualization method and proven techniques for using it to boost the accuracy and profitability of your tradesThe result of decades of research and development by mar

Rice (U. of California, Berkeley) presents a text on mathematical statistics and data analysis that emphasizes traditional topics, descriptive statistics, graphical displays, experimental design, real

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying eff

The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked, and very few books deal with these techniq

In simple and non-technical terms, the Second Edition of Data Collection and Analysis illustrates a wide range of techniques and approaches used in social research projects. Always accessible and enga

Longitudinal data analysis for biomedical and behavioral sciences This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in t

In this thrilling journey into the mysteries of our cosmos, bestselling author Michio Kaku takes us on a dizzying ride to explore black holes and time machines, multidimensional space and, most tantal

Recent years have seen a great variety of applications of DEA (Data Envelopment Analysis) for use in evaluating the performances of many different kinds of entities engaged in many different activitie

The Remote Sensing Data Book provides a unique resource of all aspects of remote sensing for the expert and non-expert alike. Organised as a dictionary, it contains over 700 alphabetically-arranged and cross-referenced entries on how remote sensing works, what kinds of data are available, and the large number of satellites and instruments from which the information is obtained. As well as short technical definitions, it also includes longer essays and reviews to give an overview of the subject. Although not a textbook in itself, the data book will serve as a valuable addition to existing textbooks for undergraduates and graduate students on geography, environmental and earth science courses that include an element of remote sensing. It will also be an essential reference for researchers and research managers at all levels using spaceborne remote sensing methods to obtain information about the earth's land, sea, ice and atmosphere.