When To Remove Outliers In Regression
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OpenIntro Statistics
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
Robust Regression and Outlier Detection
Author: Peter J. Rousseeuw
language: en
Publisher: John Wiley & Sons
Release Date: 2005-02-25
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "The writing style is clear and informal, and much of thediscussion is oriented to application. In short, the book is akeeper." –Mathematical Geology "I would highly recommend the addition of this book to thelibraries of both students and professionals. It is a usefultextbook for the graduate student, because it emphasizes both thephilosophy and practice of robustness in regression settings, andit provides excellent examples of precise, logical proofs oftheorems. . . .Even for those who are familiar with robustness, thebook will be a good reference because it consolidates the researchin high-breakdown affine equivariant estimators and includes anextensive bibliography in robust regression, outlier diagnostics,and related methods. The aim of this book, the authors tell us, is‘to make robust regression available for everyday statisticalpractice.’ Rousseeuw and Leroy have included all of thenecessary ingredients to make this happen." –Journal of the American Statistical Association
Intermediate Statistics For Dummies
Author: Deborah J. Rumsey
language: en
Publisher: John Wiley & Sons
Release Date: 2007-02-26
Need to know how to build and test models based on data? Intermediate Statistics For Dummies gives you the knowledge to estimate, investigate, correlate, and congregate certain variables based on the information at hand. The techniques you’ll learn in this book are the same techniques used by professionals in medical and scientific fields. Picking up right where Statistics For Dummies left off, this straightforward, easy-to-follow book guides you beyond Central Limit Theorem and hypothesis tests and immerses you in flavors of regression, ANOVA, and nonparametric procedures. Unlike regular statistics books, this guide provides full explanations of intermediate statistical ideas; computer input dissection; an extensive number of examples, tips, strategies, and warnings; and clear, concise step-by-step procedures—all in a language you can understand. You’ll soon discover how to: Analyze data and base models off of your data Make predictions using regression Compare many means with ANOVA Test models using Chi-square Dealing with abnormal data In addition, this book includes a list of wrong statistical conclusions and common questions that professors ask using computer output. This book also adopts a nonlinear approach, making it possible to skip to the information you need without having to read previous chapters. With Intermediate Statistics For Dummies, you’ll have all the tools you need to make important decisions in all types of professional areas—from biology and engineering to business and politics!