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Design and analysis of experiments

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Design and Analysis of Experiments

• © 2017
• Latest edition
• Angela Dean 0 ,
• Daniel Voss 1 ,
• Danel Draguljić 2

Ohio State University, Columbus, USA

You can also search for this author in PubMed   Google Scholar

Wright State University, Dayton, USA

Lancaster, usa.

• Second edition includes new material on screening experiments and analysis of mixed models, a new chapter on computer experiments, added “Using R” sections, updated SAS output, and use of SAS Proc Mixed
• Presents a step-by-step guide to design, including a planning checklist that emphasizes practical considerations
• Explains all the basics of analysis: estimation of treatment contrasts and analysis of variance, while also applying these in a wide variety of settings
• Utilizes data drawn from real experiments
• Includes supplementary material: sn.pub/extras

Part of the book series: Springer Texts in Statistics (STS)

4.94m Accesses

217 Citations

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About this book

This new, second edition includes

• an additional chapter on computer experiments
• additional "Using R” sections at the end of each chapter to illustrate R code and output 
• updated output for all SAS programs and use of SAS Proc Mixed
• new material on screening experiments and analysis of mixed models

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Design of Experiments Using R

• Design of Experiments

Choice of Test Statistic

• Analysis of Experiments
• Analysis of covariance
• Blocking factors
• Factorial experiments
• Fitting models
• Inference for Contrasts
• Planning experiments
• Polynomial regression
• Random effects

Table of contents (20 chapters)

Front matter, principles and techniques.

• Angela Dean, Daniel Voss, Danel Draguljić

Planning Experiments

Designs with one source of variation, inferences for contrasts and treatment means, checking model assumptions, experiments with two crossed treatment factors, several crossed treatment factors, polynomial regression, analysis of covariance, complete block designs, incomplete block designs, designs with two blocking factors, confounded two-level factorial experiments, confounding in general factorial experiments, fractional factorial experiments, response surface methodology, random effects and variance components, nested models, split-plot designs.

“The textbook provides a practically oriented version of design and analysis of experiments. The corresponding methods are illustrated by means of numerous simple experiments. Thus, the models and methods are equipped with many examples, exercises, numerical results and related tables and figures. ... The present volume can be recommended as textbook for lectures on models and methods of experimental design as well as handbook for use in practice.” (Kurt Marti, zbMATH 1383.62001, 2018)

Authors and Affiliations

Angela Dean

Daniel Voss

Danel Draguljić

About the authors

Bibliographic information.

Book Title : Design and Analysis of Experiments

Authors : Angela Dean, Daniel Voss, Danel Draguljić

Series Title : Springer Texts in Statistics

DOI : https://doi.org/10.1007/978-3-319-52250-0

Publisher : Springer Cham

eBook Packages : Mathematics and Statistics , Mathematics and Statistics (R0)

Copyright Information : Springer International Publishing AG 2017

Softcover ISBN : 978-3-319-52248-7 Published: 13 April 2017

eBook ISBN : 978-3-319-52250-0 Published: 05 April 2017

Series ISSN : 1431-875X

Series E-ISSN : 2197-4136

Edition Number : 2

Number of Pages : XXV, 840

Number of Illustrations : 94 b/w illustrations, 52 illustrations in colour

Topics : Statistical Theory and Methods , Probability Theory and Stochastic Processes , Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences

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A First Course in Design and Analysis of Experiments

This book by Gary W. Oehlert was first published in 2000 by W. H. Freeman. As of summer 2010, it has gone out of print. Curiously, I still like this book and would prefer to continue using it in my teaching; some of my colleagues feel the same way. And since the copyright has reverted to me, we can do that.

• You must properly attribute the work.
• You may not use this work for commercial purposes.
• You may not alter, transform, or build upon this work.

A complete description of the license may be found at the Creative Commons website.

Download First Edition

You may download A First Course in Design and Analysis of Experiments by clicking here (1.9 MB PDF).

Download Draft Second Edition

The designation "draft" is literal. All of the books are under active development, and you will be able to tell where I stopped revising and assembled this distribution file.

The PDF versions of the text include links to (some of) the material in the Examples supplement. The "local" version of the text tries to link to the local files in the RExamples subdirectory, and the "web" version of the text tries to link to files at www.stat.umn.edu/~gary/book/RExamples. The advantage of the local version is that you can use it without a network connection, but some platforms (iOS in particular) seem to make it very hard to use local files.

Whether these links work seems to be hit or miss. For example, I use a Mac, and the links work when the text is viewed using Adobe Reader, but they don't work when using Preview. On Linux, the local links didn't work using Xpdf but the web links did, while both worked under "Document Viewer". I really don't know what happens under iOS, Android, or Windows, but I'm guessing that some of it will work.

Download R Package (with data) for Second Edition

The R-package cfcdae (Companion to A First Course in Design and Analysis of Experiments) contains all of the data from the draft second edition of the book along with a handful of useful functions. (Many of these functions have analogs in other packages, they just do things the way I like.)

You may download cfcdae by clicking here

This package is in source format. Download the package and save the file into a place where R can find it (e.g., your home directory or the desktop). Start R, set the working directory to that location (e.g., use setwd(), and then use install.packages("oehlert_1..4-11.tar.gz",repos=NULL,type="source") (The repos=NULL says not to find it online but to look for the package in the local files; the type="source" tells R the file format.) Once the package is installed, you can do library(cfcdae) to load the library.

Download Data from first edition

All of the individual text data sets accessible via the web as above are also available in a single zip archive

Russ Lenth at the University of Iowa has also provided an R package that include the data sets from the book. oehlert_1.02.tar.gz Download the package and save the file into a place where R can find it (e.g., your home directory or the desktop). Start R, set the working directory to that location (e.g., use setwd(), and then use install.packages("oehlert_1.02.tar.gz",repos=NULL,type="source") (The repos=NULL says not to find it online but to look for the package in the local files; the type="source" tells R the file format.) Once the package is installed, you can do library(oehlert) from within R to load all of the data. At that point, the command pr17.4 should give you problem 4 from chapter 17.

Note that the data set names, variable names, and variable codings in oehlert.Rdata and the direct-web-accessible data may not be the same.

oehlert-data.sas An Ascii text file in SAS format. Oehlert-SAS.zip A zip archive of individual SAS data files. Again, thanks to Russ Lenth for these files.

Single text file This is in the MacAnova matread format.

Both the SAS data format and the MacAnova matread format are plain text files. You can download either and then cut/paste if you need to put the data into another format.

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