Exploring Data Tables Trends And Shapes

Author : David C. Hoaglin,Frederick Mosteller,John W. Tukey
Publisher : John Wiley & Sons
Page : 564 pages
File Size : 48,6 Mb
Release : 2011-09-28
Category : Mathematics
ISBN : 9781118150696

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Exploring Data Tables, Trends, and Shapes by David C. Hoaglin,Frederick Mosteller,John W. Tukey Pdf

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area." —Technometrics "This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously." —The Statistician This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.

Author : David C. Hoaglin,Frederick Mosteller,John W. Tukey
Publisher : John Wiley & Sons
Page : 484 pages
File Size : 51,6 Mb
Release : 2000-06-02
Category : Mathematics
ISBN : 9780471384915

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Understanding Robust and Exploratory Data Analysis by David C. Hoaglin,Frederick Mosteller,John W. Tukey Pdf

Originally published in hardcover in 1982, this book is now offered in a Wiley Classics Library edition. A contributed volume, edited by some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use exploratory data analysis and robust and resistant methods in statistical practice.

Author : Wendy L. Martinez,Angel R. Martinez,Jeffrey Solka
Publisher : CRC Press
Page : 686 pages
File Size : 41,9 Mb
Release : 2017-08-07
Category : Mathematics
ISBN : 9781315349848

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Exploratory Data Analysis with MATLAB by Wendy L. Martinez,Angel R. Martinez,Jeffrey Solka Pdf

Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data

Author : C. N. Hewitt
Publisher : Springer
Page : 315 pages
File Size : 48,8 Mb
Release : 2012-12-06
Category : Science
ISBN : 9789401129206

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Methods of Environmental Data Analysis by C. N. Hewitt Pdf

ENVIRONMENTAL MANAGEMENT SERIES The current expansion of both public and scientific interest in environ mental issues has not been accompanied by a commensurate production of adequate books, and those which are available are widely variable in approach and depth. The Environmental Management Series has been established with a view to co-ordinating a series of volumes dealing with each topic within the field in some depth. It is hoped that this Series will provide a uniform and quality coverage and that, over a period of years, it will build up to form a library of reference books covering most of the major topics within this diverse field. It is envisaged that the books will be of single, or dual authorship, or edited volumes as appropriate for respective topics. The level of presentation will be advanced, the books being aimed primarily at a research/consultancy readership. The coverage will include all aspects of environmental science and engineering pertinent to manage ment and monitoring of the natural and man-modified environment, as well as topics dealing with the political. t:conomic, legal and social con siderations pertaining to environmental management.

Author : Jane; Marsh Elliott (Catherine)
Publisher : Polity
Page : 329 pages
File Size : 45,6 Mb
Release : 2009
Category : Electronic
ISBN : 9780745622835

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Exploring Data: An Introduction to Data Analysis for Social Scientists by Jane; Marsh Elliott (Catherine) Pdf

Author : Robert P. Haining,Robert Haining
Publisher : Cambridge University Press
Page : 436 pages
File Size : 54,6 Mb
Release : 1993-08-26
Category : Mathematics
ISBN : 0521448662

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Spatial Data Analysis in the Social and Environmental Sciences by Robert P. Haining,Robert Haining Pdf

Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data description, map interpolation, and exploratory and explanatory analyses. The book also examines spatial referencing, and methods for detecting problems, assessing their seriousness and taking appropriate action are discussed. This is an important text for any discipline requiring a broad overview of current theoretical and applied work for the analysis of spatial data sets. It will be of particular use to research workers and final year undergraduates in the fields of geography, environmental sciences and social sciences.

Author : Tamraparni Dasu,Theodore Johnson
Publisher : John Wiley & Sons
Page : 226 pages
File Size : 45,5 Mb
Release : 2003-08-01
Category : Mathematics
ISBN : 9780471458647

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Exploratory Data Mining and Data Cleaning by Tamraparni Dasu,Theodore Johnson Pdf

Written for practitioners of data mining, data cleaning and database management. Presents a technical treatment of data quality including process, metrics, tools and algorithms. Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge. Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches. Uses case studies to illustrate applications in real life scenarios. Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques. Exploratory Data Mining and Data Cleaning will serve as an important reference for serious data analysts who need to analyze large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large scale data analys is and data mining.

Author : Ronald K. Pearson
Publisher : CRC Press
Page : 548 pages
File Size : 52,8 Mb
Release : 2018-05-04
Category : Business & Economics
ISBN : 9780429847035

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Exploratory Data Analysis Using R by Ronald K. Pearson Pdf

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data. The book begins with a detailed overview of data, exploratory analysis, and R, as well as graphics in R. It then explores working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. The book ends with a chapter on "keeping it all together" that includes managing the R installation, managing files, documenting, and an introduction to reproducible computing. The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. it keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available. About the Author: Ronald K. Pearson holds the position of Senior Data Scientist with GeoVera, a property insurance company in Fairfield, California, and he has previously held similar positions in a variety of application areas, including software development, drug safety data analysis, and the analysis of industrial process data. He holds a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and has published conference and journal papers on topics ranging from nonlinear dynamic model structure selection to the problems of disguised missing data in predictive modeling. Dr. Pearson has authored or co-authored books including Exploring Data in Engineering, the Sciences, and Medicine (Oxford University Press, 2011) and Nonlinear Digital Filtering with Python. He is also the developer of the DataCamp course on base R graphics and is an author of the datarobot and GoodmanKruskal R packages available from CRAN (the Comprehensive R Archive Network).

Author : Chandan Mukherjee,Howard White,Marc Wuyts
Publisher : Routledge
Page : 515 pages
File Size : 49,5 Mb
Release : 2013-09-13
Category : Business & Economics
ISBN : 9781136144608

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Econometrics and Data Analysis for Developing Countries by Chandan Mukherjee,Howard White,Marc Wuyts Pdf

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.

Author : David C. Hoaglin,Frederick Mosteller,John W. Tukey
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 40,7 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317662

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Fundamentals of Exploratory Analysis of Variance by David C. Hoaglin,Frederick Mosteller,John W. Tukey Pdf

The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

Author : Stephen E. Fienberg,David C. Hoaglin,William H. Kruskal,Judith M. Tanur
Publisher : Springer Science & Business Media
Page : 305 pages
File Size : 41,9 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461233848

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A Statistical Model by Stephen E. Fienberg,David C. Hoaglin,William H. Kruskal,Judith M. Tanur Pdf

A large number of Mostellar's friends, colleagues, collaborators, and former students have contributed to the preparation of this volume in honor of his 70th birthday. It provides a critical assessment of Mosteller's professional and research contributions to the field of statistics and its applications.

Author : Dhammika Amaratunga,Javier Cabrera
Publisher : John Wiley & Sons
Page : 274 pages
File Size : 42,5 Mb
Release : 2004
Category : Mathematics
ISBN : 0471273988

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Exploration and Analysis of DNA Microarray and Protein Array Data by Dhammika Amaratunga,Javier Cabrera Pdf

A cutting-edge guide to the analysis of DNA microarray data Genomics is one of the major scientific revolutions of this century, and the use of microarrays to rapidly analyze numerous DNA samples has enabled scientists to make sense of mountains of genomic data through statistical analysis. Today, microarrays are being used in biomedical research to study such vital areas as a drug’s therapeutic value–or toxicity–and cancer-spreading patterns of gene activity. Exploration and Analysis of DNA Microarray and Protein Array Data answers the need for a comprehensive, cutting-edge overview of this important and emerging field. The authors, seasoned researchers with extensive experience in both industry and academia, effectively outline all phases of this revolutionary analytical technique, from the preprocessing to the analysis stage. Highlights of the text include: A review of basic molecular biology, followed by an introduction to microarrays and their preparation Chapters on processing scanned images and preprocessing microarray data Methods for identifying differentially expressed genes in comparative microarray experiments Discussions of gene and sample clustering and class prediction Extension of analysis methods to protein array data Numerous exercises for self-study as well as data sets and a useful collection of computational tools on the authors’ Web site make this important text a valuable resource for both students and professionals in the field.

Author : Roger D. Masters,Michael T. McGuire
Publisher : SIU Press
Page : 276 pages
File Size : 42,6 Mb
Release : 1994
Category : Behavior
ISBN : 0809318016

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The Neurotransmitter Revolution by Roger D. Masters,Michael T. McGuire Pdf

Extraordinary advances in neurochemistry are both transforming our understanding of human nature and creating an urgent problem. Much is now known about the ways that neurotransmitters influence normal social behavior, mental illness, and deviance. What are these discoveries about the workings of the human brain? How can they best be integrated into our legal system? These explosive issues are best understood by focusing on a single neurotransmitter like serotonin, which is associated with such diverse behaviors as dominance and leadership, seasonal depression, suicide, alcoholism, impulsive homicide, and arson. This book brings together revised papers from a conference on this theme organized by the Gruter Institute for Law and Behavioral Research, supplemented with articles by leading scholars who did not attend. Contributors include psychiatrists, neurologists, social scientists, and legal scholars. The Neurotransmitter Revolution presents a unique survey of the scientific and legal implications of research on the way serotonin combines with other factors to shape human behavior. The findings are quite different from what might have been expected even a decade ago. The neurochemistry of behavior is not the same thing as genetic determinism. On the contrary, the activity of serotonin varies from one individual to another for many reasons, including the individual’s life experience, social status, personality, and diet. And there are a number of major neurotransmitter systems, each of which interacts with the other. Behavior, culture, and the social environment can influence neurochemistry along with inheritance. Nature and nurture interact—and these interactions can be understood from a vigorously scientific point of view. The fact that our actions are heavily influenced by neurotransmitters like serotonin is bound to be disquieting. A sophisticated understanding of law and human social behavior will be needed if our society is to respond adequately to these rapid advances in our knowledge. This book is an essential step in that direction, providing the first comprehensive survey of the biochemical, social, and legal considerations arising from research on the behavioral effects of serotonin and related neurotransmitters.

Author : Dhammika Amaratunga,Javier Cabrera,Ziv Shkedy
Publisher : John Wiley & Sons
Page : 344 pages
File Size : 45,7 Mb
Release : 2014-01-27
Category : Mathematics
ISBN : 9781118364529

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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data by Dhammika Amaratunga,Javier Cabrera,Ziv Shkedy Pdf

Praise for the First Edition “…extremely well written…a comprehensiveand up-to-date overview of this important field.” –Journal of Environmental Quality Exploration and Analysis of DNA Microarray and OtherHigh-Dimensional Data, Second Edition provides comprehensivecoverage of recent advancements in microarray data analysis. Acutting-edge guide, the Second Edition demonstrates variousmethodologies for analyzing data in biomedical research and offersan overview of the modern techniques used in microarray technologyto study patterns of gene activity. The new edition answers the need for an efficient outline of allphases of this revolutionary analytical technique, frompreprocessing to the analysis stage. Utilizing research andexperience from highly-qualified authors in fields of dataanalysis, Exploration and Analysis of DNA Microarray and OtherHigh-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes adiscussion of signatures and material on gene set analysis,including network analysis New topics of coverage including ABC clustering, biclustering,partial least squares, penalized methods, ensemble methods, andenriched ensemble methods Updated exercises to deepen knowledge of the presented materialand provide readers with resources for further study The book is an ideal reference for scientists in biomedical andgenomics research fields who analyze DNA microarrays and proteinarray data, as well as statisticians and bioinformaticspractitioners. Exploration and Analysis of DNA Microarray andOther High-Dimensional Data, Second Edition is also a usefultext for graduate-level courses on statistics, computationalbiology, and bioinformatics.

Author : Pavel V. Shevchenko
Publisher : Springer Science & Business Media
Page : 302 pages
File Size : 53,9 Mb
Release : 2011-01-19
Category : Business & Economics
ISBN : 9783642159237

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Modelling Operational Risk Using Bayesian Inference by Pavel V. Shevchenko Pdf

The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products, and changes in information technology have resulted in exposure to new risks which are very different from market and credit risks. In response, the Basel Committee on Banking Supervision has developed a new regulatory framework for capital measurement and standards for the banking sector. This has formally defined operational risk and introduced corresponding capital requirements. Many banks are undertaking quantitative modelling of operational risk using the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity of operational risk losses. There are a number of unresolved methodological challenges in the LDA implementation. Overall, the area of quantitative operational risk is very new and different methods are under hot debate. This book is devoted to quantitative issues in LDA. In particular, the use of Bayesian inference is the main focus. Though it is very new in this area, the Bayesian approach is well suited for modelling operational risk, as it allows for a consistent and convenient statistical framework for quantifying the uncertainties involved. It also allows for the combination of expert opinion with historical internal and external data in estimation procedures. These are critical, especially for low-frequency/high-impact operational risks. This book is aimed at practitioners in risk management, academic researchers in financial mathematics, banking industry regulators and advanced graduate students in the area. It is a must-read for anyone who works, teaches or does research in the area of financial risk.