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Regression Graphics


Regression Graphics
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An Introduction To Regression Graphics


An Introduction To Regression Graphics
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Author : R. Dennis Cook
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25

An Introduction To Regression Graphics written by R. Dennis Cook and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.


Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.



Regression Graphics


Regression Graphics
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Author : R. Dennis Cook
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25

Regression Graphics written by R. Dennis Cook and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.


An exploration of regression graphics through computer graphics. Recent developments in computer technology have stimulated new and exciting uses for graphics in statistical analyses. Regression Graphics, one of the first graduate-level textbooks on the subject, demonstrates how statisticians, both theoretical and applied, can use these exciting innovations. After developing a relatively new regression context that requires few scope-limiting conditions, Regression Graphics guides readers through the process of analyzing regressions graphically and assessing and selecting models. This innovative reference makes use of a wide range of graphical tools, including 2D and 3D scatterplots, 3D binary response plots, and scatterplot matrices. Supplemented by a companion ftp site, it features numerous data sets and applied examples that are used to elucidate the theory. Other important features of this book include: * Extensive coverage of a relatively new regression context based on dimension-reduction subspaces and sufficient summary plots * Graphical regression, an iterative visualization process for constructing sufficient regression views * Graphics for regressions with a binary response * Graphics for model assessment, including residual plots * Net-effects plots for assessing predictor contributions * Graphics for predictor and response transformations * Inverse regression methods * Access to a Web site of supplemental plots, data sets, and 3D color displays. An ideal text for students in graduate-level courses on statistical analysis, Regression Graphics is also an excellent reference for professional statisticians.



Applied Regression Including Computing And Graphics


Applied Regression Including Computing And Graphics
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Author : R. Dennis Cook
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25

Applied Regression Including Computing And Graphics written by R. Dennis Cook and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.


A step-by-step guide to computing and graphics in regression analysis In this unique book, leading statisticians Dennis Cook and Sanford Weisberg expertly blend regression fundamentals and cutting-edge graphical techniques. They combine and up- date most of the material from their widely used earlier work, An Introduction to Regression Graphics, and Weisberg's Applied Linear Regression; incorporate the latest in statistical graphics, computing, and regression models; and wind up with a modern, fully integrated approach to one of the most important tools of data analysis. In 23 concise, easy-to-digest chapters, the authors present:? A wealth of simple 2D and 3D graphical techniques, helping visualize results through graphs * An improved version of the user-friendly Arc software, which lets readers promptly implement new ideas * Complete coverage of regression models, including logistic regression and generalized linear models * More than 300 figures, easily reproducible on the computer * Numerous examples and problems based on real data * A companion Web site featuring free software and advice, available at www.wiley.com/mathem atics Accessible, self-contained, and fully referenced, Applied Regression Including Computing and Graphics assumes only a first course in basic statistical methods and provides a bona fide user manual for the Arc software. It is an invaluable resource for anyone interested in learning how to analyze regression problems with confidence and depth.



Regression With Graphics


Regression With Graphics
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Author : Lawrence C. Hamilton
language : en
Publisher: Brooks/Cole
Release Date : 1992

Regression With Graphics written by Lawrence C. Hamilton and has been published by Brooks/Cole this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.


This text demonstrates how computing power has expanded the role of graphics in analyzing, exploring, and experimenting with raw data. It is primarily intended for students whose research requires more than an introductory statistics course, but who may not have an extensive background in rigorous mathematics. It's also suitable for courses with students of varying mathematical abilities. Hamilton provides students with a practical, realistic, and graphical approach to regression analysis so that they are better prepared to solve real, sometimes messy problems. For students and professors who prefer a heavier mathematical emphasis, the author has included optional sections throughout the text where the formal, mathematical development of the material is explained in greater detail. REGRESSION WITH GRAPHICS is appropriate for use with any (or no) statistical computer package. However, Hamilton used STAT A in the development of the text due to its ease of application and sophisticated graphics capabilities. (STATA is available in a student package from Duxbury including a tutorial by the same author: Hamilton, STATISTICS WITH STAT A, 5.0, 1998; ISBN: 0-534-31874-6.)



Graphics For Statistics And Data Analysis With R


Graphics For Statistics And Data Analysis With R
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Author : Kevin J. Keen
language : en
Publisher: CRC Press
Release Date : 2018-09-26

Graphics For Statistics And Data Analysis With R written by Kevin J. Keen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 with Mathematics categories.


Praise for the First Edition "The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is particularly useful to assist readers’ understanding of the graphical techniques discussed in the book. ... It not only summarises graphical techniques, but it also serves as a practical reference for researchers and graduate students with an interest in data display." -Han Lin Shang, Journal of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print. Features Emphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in R Presents technical details on topics such as: the estimation of quantiles, nonparametric and parametric density estimation; diagnostic plots for the simple linear regression model; polynomial regression, splines, and locally weighted polynomial regression for producing a smooth curve; Trellis graphics for multivariate data Provides downloadable R code and data for figures at www.graphicsforstatistics.com Kevin J. Keen is a Professor of Mathematics and Statistics at the University of Northern British Columbia (Prince George, Canada) and an Accredited Professional StatisticianTM by the Statistical Society of Canada and the American Statistical Association.



Graphics For Statistics And Data Analysis With R


Graphics For Statistics And Data Analysis With R
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Author : Kevin J Keen
language : en
Publisher: CRC Press
Release Date : 2010-04-26

Graphics For Statistics And Data Analysis With R written by Kevin J Keen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-26 with Mathematics categories.


Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.



Using R For Data Management Statistical Analysis And Graphics


Using R For Data Management Statistical Analysis And Graphics
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Author : Nicholas J. Horton
language : en
Publisher: CRC Press
Release Date : 2010-07-28

Using R For Data Management Statistical Analysis And Graphics written by Nicholas J. Horton and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-28 with Mathematics categories.


Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphicsUsing R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes



R In Action Third Edition


R In Action Third Edition
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Author : Robert I. Kabacoff
language : en
Publisher: Simon and Schuster
Release Date : 2022-06-28

R In Action Third Edition written by Robert I. Kabacoff and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Computers categories.


R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for commercial environments. In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean, manage, and analyze data with R Use the ggplot2 package for graphs and visualizations Solve data management problems using R functions Fit and interpret regression models Test hypotheses and estimate confidence Simplify complex multivariate data with principal components and exploratory factor analysis Make predictions using time series forecasting Create dynamic reports and stunning visualizations Techniques for debugging programs and creating packages R in Action, Third Edition makes learning R quick and easy. That’s why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you’ll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R’s state-of-the-art graphing capabilities with the ggplot2 package. About the technology Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical problems without forcing you to think like a software engineer. About the book R in Action, Third Edition teaches you how to do statistical analysis and data visualization using R and its popular tidyverse packages. In it, you’ll investigate real-world data challenges, including forecasting, data mining, and dynamic report writing. This revised third edition adds new coverage for graphing with ggplot2, along with examples for machine learning topics like clustering, classification, and time series analysis. What's inside Clean, manage, and analyze data Use the ggplot2 package for graphs and visualizations Techniques for debugging programs and creating packages A complete learning resource for R and tidyverse About the reader Requires basic math and statistics. No prior experience with R needed. About the author Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University and a seasoned data scientist with more than 20 years of experience. Table of Contents PART 1 GETTING STARTED 1 Introduction to R 2 Creating a dataset 3 Basic data management 4 Getting started with graphs 5 Advanced data management PART 2 BASIC METHODS 6 Basic graphs 7 Basic statistics PART 3 INTERMEDIATE METHODS 8 Regression 9 Analysis of variance 10 Power analysis 11 Intermediate graphs 12 Resampling statistics and bootstrapping PART 4 ADVANCED METHODS 13 Generalized linear models 14 Principal components and factor analysis 15 Time series 16 Cluster analysis 17 Classification 18 Advanced methods for missing data PART 5 EXPANDING YOUR SKILLS 19 Advanced graphs 20 Advanced programming 21 Creating dynamic reports 22 Creating a package



Applied Linear Regression


Applied Linear Regression
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Author : Sanford Weisberg
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-25

Applied Linear Regression written by Sanford Weisberg and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-25 with Mathematics categories.


Praise for the Third Edition "...this is an excellent book which could easily be used as a course text..." —International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illustrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. While maintaining the accessible appeal of each previous edition,Applied Linear Regression, Fourth Edition features: Graphical methods stressed in the initial exploratory phase, analysis phase, and summarization phase of an analysis In-depth coverage of parameter estimates in both simple and complex models, transformations, and regression diagnostics Newly added material on topics including testing, ANOVA, and variance assumptions Updated methodology, such as bootstrapping, cross-validation binomial and Poisson regression, and modern model selection methods Applied Linear Regression, Fourth Edition is an excellent textbook for upper-undergraduate and graduate-level students, as well as an appropriate reference guide for practitioners and applied statisticians in engineering, business administration, economics, and the social sciences.



Plots Transformations And Regression


Plots Transformations And Regression
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Author : Anthony Curtis Atkinson
language : en
Publisher:
Release Date : 1942

Plots Transformations And Regression written by Anthony Curtis Atkinson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1942 with categories.