Statistical Data Cleaning with Applications in R

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118897157
Pages : 320 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.9/5 (897 users download)


Download Statistical Data Cleaning with Applications in R by Mark van der Loo PDF/Ebook Free clicking on the below button will initiate the downloading process of Statistical Data Cleaning with Applications in R by Mark van der Loo. This book is available in ePub and PDF format with a single click unlimited downloads. A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning with Applications in R brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. Supported by an accompanying website featuring data and R code. Statistical Data Cleaning with Applications in R enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. This book can also be used as material for courses in both data cleaning and data analysis.


Statistical Shape Analysis

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9780470699621
Pages : 496 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.9/5 (699 users download)


Download Statistical Shape Analysis by Ian L. Dryden PDF/Ebook Free clicking on the below button will initiate the downloading process of Statistical Shape Analysis by Ian L. Dryden. This book is available in ePub and PDF format with a single click unlimited downloads. Originally published as: Statistical shape analysis, 1998


Foundations of Linear and Generalized Linear Models

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118730034
Pages : 480 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.3/5 (73 users download)


Download Foundations of Linear and Generalized Linear Models by Alan Agresti PDF/Ebook Free clicking on the below button will initiate the downloading process of Foundations of Linear and Generalized Linear Models by Alan Agresti. This book is available in ePub and PDF format with a single click unlimited downloads. A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.


Handbook of Regression Analysis With Applications in R

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781119392378
Pages : 384 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.9/5 (392 users download)


Download Handbook of Regression Analysis With Applications in R by Samprit Chatterjee PDF/Ebook Free clicking on the below button will initiate the downloading process of Handbook of Regression Analysis With Applications in R by Samprit Chatterjee. This book is available in ePub and PDF format with a single click unlimited downloads. Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors’ thorough treatments of “classic” regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Further, methods that have become prominent in the last 15-30 years that are designed for analyses on often-large data sets and can take advantage of flexibility in modeling were not covered, including smoothing, tree- based, and regularization methods, all of which are increasingly becoming part of the data analysis toolkit. Examples are drawn from a wide variety of application areas using real data sets and all of the R code is provided. The book will be of interest to data scientists as well as in regression analysis courses at the graduate and undergraduate level.


Exploratory Data Mining and Data Cleaning

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9780471458647
Pages : 203 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.5/5 (458 users download)


Download Exploratory Data Mining and Data Cleaning by Tamraparni Dasu PDF/Ebook Free clicking on the below button will initiate the downloading process of Exploratory Data Mining and Data Cleaning by Tamraparni Dasu. This book is available in ePub and PDF format with a single click unlimited downloads. Written for practitioners of data mining, data cleaning anddatabase management. Presents a technical treatment of data quality includingprocess, metrics, tools and algorithms. Focuses on developing an evolving modeling strategy through aniterative data exploration loop and incorporation of domainknowledge. Addresses methods of detecting, quantifying and correcting dataquality issues that can have a significant impact on findings anddecisions, using commercially available tools as well as newalgorithmic approaches. Uses case studies to illustrate applications in real lifescenarios. Highlights new approaches and methodologies, such as theDataSphere space partitioning and summary based analysistechniques. Exploratory Data Mining and Data Cleaning will serve as animportant reference for serious data analysts who need to analyzelarge amounts of unfamiliar data, managers of operations databases,and students in undergraduate or graduate level courses dealingwith large scale data analys is and data mining.


Handbook of Statistics

Author :
Publisher : Elsevier
Release Date :
ISBN 10 : 9780444634412
Pages : 412 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.3/5 (634 users download)


Download Handbook of Statistics by PDF/Ebook Free clicking on the below button will initiate the downloading process of Handbook of Statistics by . This book is available in ePub and PDF format with a single click unlimited downloads. R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. Addresses data examples that can be downloaded directly from the R website No other source is needed to gain practical experience Focus on the essentials in graphical outlays


A Primer on Experiments with Mixtures

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9780470907429
Pages : 372 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.0/5 (97 users download)


Download A Primer on Experiments with Mixtures by John A. Cornell PDF/Ebook Free clicking on the below button will initiate the downloading process of A Primer on Experiments with Mixtures by John A. Cornell. This book is available in ePub and PDF format with a single click unlimited downloads. The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents, multicomponent constraints, and multiple lattice designs for major and minor component classifications Techniques for analyzing mixture data such as model reduction and screening components, as well as additional topics such as measuring the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance for fitting data Each chapter concludes with a summary and appendices with details on the technical aspects of the material. Throughout the book, exercise sets with selected answers allow readers to test their comprehension of the material, and References and Recommended Reading sections outline further resources for study of the presented topics. A Primer on Experiments with Mixtures is an excellent book for one-semester courses on mixture designs and can also serve as a supplement for design of experiments courses at the upper-undergraduate and graduate levels. It is also a suitable reference for practitioners and researchers who have an interest in experiments with mixtures and would like to learn more about the related mixture designs and models.


Bayesian Analysis of Stochastic Process Models

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118304037
Pages : 320 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.0/5 (34 users download)


Download Bayesian Analysis of Stochastic Process Models by David Insua PDF/Ebook Free clicking on the below button will initiate the downloading process of Bayesian Analysis of Stochastic Process Models by David Insua. This book is available in ePub and PDF format with a single click unlimited downloads. Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.


Data Mining for Business Applications

Author :
Publisher : IOS Press
Release Date :
ISBN 10 : 9781607506324
Pages : 181 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.0/5 (56 users download)


Download Data Mining for Business Applications by Carlos A. Mota Soares PDF/Ebook Free clicking on the below button will initiate the downloading process of Data Mining for Business Applications by Carlos A. Mota Soares. This book is available in ePub and PDF format with a single click unlimited downloads. Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.


A History of Probability and Statistics and Their Applications before 1750

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9780471725176
Pages : 608 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.2/5 (725 users download)


Download A History of Probability and Statistics and Their Applications before 1750 by Anders Hald PDF/Ebook Free clicking on the below button will initiate the downloading process of A History of Probability and Statistics and Their Applications before 1750 by Anders Hald. This book is available in ePub and PDF format with a single click unlimited downloads. 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. From the Reviews of History of Probability and Statistics and Their Applications before 1750 "This is a marvelous book . . . Anyone with the slightest interest in the history of statistics, or in understanding how modern ideas have developed, will find this an invaluable resource." –Short Book Reviews of ISI


An Introduction to Probability and Statistics

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118799642
Pages : 688 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.9/5 (799 users download)


Download An Introduction to Probability and Statistics by Vijay K. Rohatgi PDF/Ebook Free clicking on the below button will initiate the downloading process of An Introduction to Probability and Statistics by Vijay K. Rohatgi. This book is available in ePub and PDF format with a single click unlimited downloads. This Third Edition provides a solid and well-balancedintroduction to probability theory and mathematicalstatistics. The book is divided into three parts: Chapters1-6 form the core of probability fundamentals and foundations;Chapters 7-11 cover statistics inference; and the remainingchapters focus on special topics. For course sequences thatseparate probability and mathematics statistics, the first part ofthe book can be used for a course in probability theory, followedby a course in mathematical statistics based on the second part,and possibly, one or more chapters on special topics. Thebook contains over 550 problems, 350 worked-out examples, and 200side notes for reader reference. Numerous figures have beenadded to illustrate examples and proofs, and answers to selectproblems are now included. Many parts of the book haveundergone substantial rewriting, and the book has also beenreorganized. Chapters 6 and 7 have been interchanged to emphasizethe role of asymptotics in statistics, and the new Chapter 7contains all of the needed basic material on asymptotics. Chapter 6 also includes new material on resampling, specificallybootstrap. The new Further Results chapter include someestimation procedures such as M-estimatesand bootstrapping. A new chapter on regression analysishas also been added and contains sections on linear regression,multiple regression, subset regression, logistic regression, andPoisson regression.


Data Analysis, Machine Learning and Applications

Author :
Publisher : Springer Science & Business Media
Release Date :
ISBN 10 : 9783540782469
Pages : 719 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.8/5 (782 users download)


Download Data Analysis, Machine Learning and Applications by Christine Preisach PDF/Ebook Free clicking on the below button will initiate the downloading process of Data Analysis, Machine Learning and Applications by Christine Preisach. This book is available in ePub and PDF format with a single click unlimited downloads. Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.


Nonparametric Statistical Methods

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118553299
Pages : 848 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.5/5 (553 users download)


Download Nonparametric Statistical Methods by Myles Hollander PDF/Ebook Free clicking on the below button will initiate the downloading process of Nonparametric Statistical Methods by Myles Hollander. This book is available in ePub and PDF format with a single click unlimited downloads. Praise for the Second Edition “This book should be an essential part of the personallibrary of every practicingstatistician.”—Technometrics Thoroughly revised and updated, the new edition of NonparametricStatistical Methods includes additional modern topics andprocedures, more practical data sets, and new problems fromreal-life situations. The book continues to emphasize theimportance of nonparametric methods as a significant branch ofmodern statistics and equips readers with the conceptual andtechnical skills necessary to select and apply the appropriateprocedures for any given situation. Written by leading statisticians, Nonparametric StatisticalMethods, Third Edition provides readers with crucialnonparametric techniques in a variety of settings, emphasizing theassumptions underlying the methods. The book provides an extensivearray of examples that clearly illustrate how to use nonparametricapproaches for handling one- or two-sample location and dispersionproblems, dichotomous data, and one-way and two-way layoutproblems. In addition, the Third Edition features: The use of the freely available R software to aid incomputation and simulation, including many new R programs writtenexplicitly for this new edition New chapters that address density estimation, wavelets,smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science,astronomy, biology, criminology, education, engineering,environmental science, geology, home economics, medicine,oceanography, physics, psychology, sociology, and spacescience Nonparametric Statistical Methods, Third Edition is anexcellent reference for applied statisticians and practitioners whoseek a review of nonparametric methods and their relevantapplications. The book is also an ideal textbook forupper-undergraduate and first-year graduate courses in appliednonparametric statistics.


Handbook of Statistical Analysis and Data Mining Applications

Author :
Publisher : Academic Press
Release Date :
ISBN 10 : 0080912036
Pages : 864 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.8/5 (8 users download)


Download Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet PDF/Ebook Free clicking on the below button will initiate the downloading process of Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet. This book is available in ePub and PDF format with a single click unlimited downloads. The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book


Database Systems for Advanced Applications

Author :
Publisher : Springer
Release Date :
ISBN 10 : 9783642008870
Pages : 797 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.0/5 (8 users download)


Download Database Systems for Advanced Applications by Xiaofang Zhou PDF/Ebook Free clicking on the below button will initiate the downloading process of Database Systems for Advanced Applications by Xiaofang Zhou. This book is available in ePub and PDF format with a single click unlimited downloads. This book constitutes the refereed proceedings of the 14th International Conference on Database Systems for Advanced Applications, DASFAA 2009, held in Brisbane, Australia, in April 2009. The 39 revised full papers and 22 revised short papers presented together with 3 invited keynote papers, 9 demonstration papers, 3 tutorial abstracts, and one panel abstract were carefully reviewed and selected from 186 submissions. The papers are organized in topical sections on uncertain data and ranking, sensor networks, graphs, RFID and data streams, skyline and rising stars, parallel and distributed processing, mining and analysis, XML query, privacy, XML keyword search and ranking, Web and Web services, XML data processing, and multimedia.


Statistics for Big Data For Dummies

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9781118940013
Pages : 384 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.4/5 (94 users download)


Download Statistics for Big Data For Dummies by Alan Anderson PDF/Ebook Free clicking on the below button will initiate the downloading process of Statistics for Big Data For Dummies by Alan Anderson. This book is available in ePub and PDF format with a single click unlimited downloads. The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word "statistics" alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.


Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment

Author :
Publisher : John Wiley & Sons
Release Date :
ISBN 10 : 9780470857663
Pages : 502 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.5/5 (857 users download)


Download Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment by Lutz Edler PDF/Ebook Free clicking on the below button will initiate the downloading process of Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment by Lutz Edler. This book is available in ePub and PDF format with a single click unlimited downloads. Human health risk assessment involves the measuring of risk of exposure to disease, with a view to improving disease prevention. Mathematical, biological, statistical, and computational methods play a key role in exposure assessment, hazard assessment and identification, and dose-response modelling. Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment is a comprehensive text that accounts for the wealth of new biological data as well as new biological, toxicological, and medical approaches adopted in risk assessment. It provides an authoritative compendium of state-of-the-art methods proposed and used, featuring contributions from eminent authors with varied experience from academia, government, and industry. Provides a comprehensive summary of currently available quantitative methods for risk assessment of both cancer and non-cancer problems. Describes the applications and the limitations of current mathematical modelling and statistical analysis methods (classical and Bayesian). Includes an extensive introduction and discussion to each chapter. Features detailed studies of risk assessments using biologically-based modelling approaches. Discusses the varying computational aspects of the methods proposed. Provides a global perspective on human health risk assessment by featuring case studies from a wide range of countries. Features an extensive bibliography with links to relevant background information within each chapter. Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment will appeal to researchers and practitioners in public health & epidemiology, and postgraduate students alike. It will also be of interest to professionals working in risk assessment agencies.


Popular Ebook