A Practitioners Guide To Resampling For Data Analysis Data Mining And Modeling

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A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling

Author : Phillip I. Good
Publisher : Chapman and Hall/CRC
ISBN 13 : 9780367803674
Total Pages : 224 pages
Book Rating : 4.8/5 (36 download)

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Book Synopsis A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling by : Phillip I. Good

Download or read book A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling written by Phillip I. Good and published by Chapman and Hall/CRC. This book was released on 2012 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distribution-free resampling methods--permutation tests, decision trees, and the bootstrap--are used today in virtually every research area. A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling explains how to use the bootstrap to estimate the precision of sample-based estimates and to determine sample size, data permutations to test hypotheses, and the readily-interpreted decision tree to replace arcane regression methods.Highlights Each chapter contains dozens of thought provoking questions, along with applicable R and Stata codeMethods are illustrated with examples from agriculture, audits, bird migration, clinical trials, epidemiology, image processing, immunology, medicine, microarrays and gene selectionLists of commercially available software for the bootstrap, decision trees, and permutation tests are incorporated in the textAccess to APL, MATLAB, and SC code for many of the routines is provided on the author's websiteThe text covers estimation, two-sample and k-sample univariate, and multivariate comparisons of means and variances, sample size determination, categorical data, multiple hypotheses, and model buildingStatistics practitioners will find the methods described in the text easy to learn and to apply in a broad range of subject areas from A for Accounting, Agriculture, Anthropology, Aquatic science, Archaeology, Astronomy, and Atmospheric science to V for Virology and Vocational Guidance, and Z for Zoology.Practitioners and research workers and in the biomedical, engineering and social sciences, as well as advanced students in biology, business, dentistry, medicine, psychology, public health, sociology, and statistics will find an easily-grasped guide to estimation, testing hypotheses and model building.

A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling

Author : Phillip Good
Publisher : Chapman & Hall/CRC
ISBN 13 : 9780367382483
Total Pages : 0 pages
Book Rating : 4.3/5 (824 download)

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Book Synopsis A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling by : Phillip Good

Download or read book A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling written by Phillip Good and published by Chapman & Hall/CRC. This book was released on 2019-06-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resampling methods--techniques for repeatedly resampling data to obtain results--are being used in virtually every research area. This practical guide discusses the applications of these methods in a wide variety of subject areas. Each chapter contains a wealth of examples along with R and Stata code for implementing the techniques. Written by a leading authority in the field, the text covers estimation, two-sample and k-sample univariate, and multivariate comparisons of means and variances, sample size determination, categorical data analysis, multiple hypotheses, and model building.

Combinatorial Inference in Geometric Data Analysis

Author : Brigitte Le Roux
Publisher : CRC Press
ISBN 13 : 1351651331
Total Pages : 234 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Combinatorial Inference in Geometric Data Analysis by : Brigitte Le Roux

Download or read book Combinatorial Inference in Geometric Data Analysis written by Brigitte Le Roux and published by CRC Press. This book was released on 2019-03-20 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial framework. It focuses particularly on the comparison of a group of observations to a reference population (combinatorial test) or to a reference value of a location parameter (geometric test), and on problems of homogeneity, that is the comparison of several groups for two basic designs. These methods involve the use of combinatorial procedures to build a reference set in which we place the data. The chosen test statistics lead to original extensions, such as the geometric interpretation of the observed level, and the construction of a compatibility region. Features: Defines precisely the object under study in the context of multidimensional procedures, that is clouds of points Presents combinatorial tests and related computations with R and Coheris SPAD software Includes four original case studies to illustrate application of the tests Includes necessary mathematical background to ensure it is self–contained This book is suitable for researchers and students of multivariate statistics, as well as applied researchers of various scientific disciplines. It could be used for a specialized course taught at either master or PhD level.

The A-Z of Error-Free Research

Author : Phillip I. Good
Publisher : CRC Press
ISBN 13 : 1439897379
Total Pages : 273 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis The A-Z of Error-Free Research by : Phillip I. Good

Download or read book The A-Z of Error-Free Research written by Phillip I. Good and published by CRC Press. This book was released on 2012-08-01 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R Code The A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication. Transition from Student to Researcher Helping you become a confident researcher, the book begins with an overview of when—and when not—to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.

Robust Multivariate Analysis

Author : David J. Olive
Publisher : Springer
ISBN 13 : 3319682539
Total Pages : 508 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Robust Multivariate Analysis by : David J. Olive

Download or read book Robust Multivariate Analysis written by David J. Olive and published by Springer. This book was released on 2017-11-28 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.

Statistical Roundtables

Author : Christine M. Anderson-Cook
Publisher : Quality Press
ISBN 13 : 087389930X
Total Pages : 552 pages
Book Rating : 4.8/5 (738 download)

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Book Synopsis Statistical Roundtables by : Christine M. Anderson-Cook

Download or read book Statistical Roundtables written by Christine M. Anderson-Cook and published by Quality Press. This book was released on 2016-04-22 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quality Progress, the flagship journal of ASQ, has been publishing the column Statistics Roundtable since 1999. With over 130 contributions from leading authors in applied statistics, the column has been highly successful and widely read. This book collects 90 of the most interesting and useful articles on some key topics. The editors have constructed this book to be a resource for statisticians and practitioners alike with short, accessible, practical advice in important core areas of statistics from world-renowned experts. This book is intended to be an informative read, with bite-sized columns, as well as a starting point for deeper exploration of key statistical areas. The book contains nine chapters with collections of articles on the following topics: Statistical engineering Data quality and measurement Data collection Key statistical tools Quality control Reliability Multiple response and meta-analysis Applications Communication and training Chapter introductions provide a quick overview of the material contained in the columns of that chapter, as well as complementary articles for that topic that appear elsewhere in the book. Also included at the end of the each chapter introduction is a short list of key references that can provide additional details or examples for material in the topic area.

Medical Biostatistics

Author : Abhaya Indrayan
Publisher : CRC Press
ISBN 13 : 149879954X
Total Pages : 984 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Medical Biostatistics by : Abhaya Indrayan

Download or read book Medical Biostatistics written by Abhaya Indrayan and published by CRC Press. This book was released on 2017-11-27 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.

Data Mining and Statistical Analysis Using SQL

Author : John Lovett
Publisher : Apress
ISBN 13 : 1430208554
Total Pages : 423 pages
Book Rating : 4.4/5 (32 download)

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Book Synopsis Data Mining and Statistical Analysis Using SQL by : John Lovett

Download or read book Data Mining and Statistical Analysis Using SQL written by John Lovett and published by Apress. This book was released on 2008-01-01 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is not just another theoretical text on statistics or data mining. Instead, it's designed for database administrators who want to buttress their understanding of statistics to support data mining and customer relationship management analytics and who want to use Structured Query Language (SQL). Each chapter is independent and self-contained with examples tailored to business applications. Each analysis technique is expressed in a mathematical format that lends itself to coding either as a database query or as a Visual Basic procedure using SQL. Each chapter includes: formulas (how to perform the required analysis, numerical example using data from a database, data visualization and presentation options (graphs, charts, tables), SQL procedures for extracting the desired results, and data mining techniques.

Concise Encyclopedia of Biostatistics for Medical Professionals

Author : Abhaya Indrayan
Publisher : CRC Press
ISBN 13 : 1315355574
Total Pages : 1589 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Concise Encyclopedia of Biostatistics for Medical Professionals by : Abhaya Indrayan

Download or read book Concise Encyclopedia of Biostatistics for Medical Professionals written by Abhaya Indrayan and published by CRC Press. This book was released on 2016-11-25 with total page 1589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concise Encyclopedia of Biostatistics for Medical Professionals focuses on conceptual knowledge and practical advice rather than mathematical details, enhancing its usefulness as a reference for medical professionals. The book defines and describes nearly 1000 commonly and not so commonly used biostatistical terms and methods arranged in alphabetical order. These range from simple terms, such as mean and median to advanced terms such as multilevel models and generalized estimating equations. Synonyms or alternative phrases for each topic covered are listed with a reference to the topic.

Becoming a Behavioral Science Researcher, Second Edition

Author : Rex B. Kline
Publisher : Guilford Publications
ISBN 13 : 1462541283
Total Pages : 377 pages
Book Rating : 4.4/5 (625 download)

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Book Synopsis Becoming a Behavioral Science Researcher, Second Edition by : Rex B. Kline

Download or read book Becoming a Behavioral Science Researcher, Second Edition written by Rex B. Kline and published by Guilford Publications. This book was released on 2019-11-12 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Students and beginning researchers often discover that their introductory statistics and methods courses have not fully equipped them to plan and execute their own behavioral research studies. This indispensable book bridges the gap between coursework and conducting independent research. With clarity and wit, the author helps the reader build needed skills to formulate a precise, meaningful research question; understand the pros and cons of widely used research designs and analysis options; correctly interpret the outcomes of statistical tests; make informed measurement choices for a particular study; manage the practical aspects of data screening and preparation; and craft effective journal articles, oral presentations, and posters. Including annotated examples and recommended readings, most chapters feature theoretical and computer-based exercises; an answer appendix at the back of the book allows readers to check their work.

Data Mining for Business Analytics

Author : Galit Shmueli
Publisher : John Wiley & Sons
ISBN 13 : 111954985X
Total Pages : 608 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Data Mining for Business Analytics by : Galit Shmueli

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-10-14 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Resampling Methods

Author : Phillip I. Good
Publisher :
ISBN 13 : 9783764342432
Total Pages : 238 pages
Book Rating : 4.3/5 (424 download)

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Book Synopsis Resampling Methods by : Phillip I. Good

Download or read book Resampling Methods written by Phillip I. Good and published by . This book was released on 2001 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Data Science

Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 794 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Introduction to Data Science by : Rafael A. Irizarry

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Data Mining for Business Analytics

Author : Galit Shmueli
Publisher : John Wiley & Sons
ISBN 13 : 1118729277
Total Pages : 560 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Data Mining for Business Analytics by : Galit Shmueli

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-04-18 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "…full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.

An Introduction to Statistical Learning

Author : Gareth James
Publisher : Springer Nature
ISBN 13 : 3031387473
Total Pages : 617 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis An Introduction to Statistical Learning by : Gareth James

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Applied Predictive Modeling

Author : Max Kuhn
Publisher : Springer Science & Business Media
ISBN 13 : 1461468493
Total Pages : 595 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Predictive Modeling by : Max Kuhn

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Practical Statistics for Data Scientists

Author : Peter Bruce
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491952911
Total Pages : 395 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce

Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data