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SAS System for Regression, Second Edition (Sas Series in Statistical Applications)
 
 
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SAS System for Regression, Second Edition (Sas Series in Statistical Applications) [Paperback]

Rudolf J. Freund (Author), Ramon C. Littell (Author)
4.3 out of 5 stars  See all reviews (3 customer reviews)


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Paperback, January 29, 1991 --  

Book Description

1555444296 978-1555444297 January 29, 1991 2nd
Experienced SAS System users will find this an invaluable guide to SAS procedures for performing regression analyses. Simple and multiple variable models are discussed as well as polynomial models, log-linear models, spline functions, and restricted linear models. With this book you will become a pro at using various MODEL statement options with the REG procedure and creating data sets with the OUTPUT statement, detecting multicollinearity and combating its effects,and fitting a growth curve with the NLIN procedure.

Supports releases 6.07 and higher of SAS software.



Editorial Reviews

Review

“…a user-friendly text…easy-to-use…” (Statistical Methods in Medical Research, No.13, 2004)

"This example-driven volume offers instruction on a wide variety of regression analyses using SAS software." (SciTech Book News, Vol. 25, No. 3, September 2001)

"Any statistician or SAS user who does regression analysis must own this book." (Technometrics, Vol. 43, No. 4, November 2001)

"...an excellent introduction to regression and its implementation in SAS." (Journal of the American Statistical Association, December 2001) --This text refers to an alternate Paperback edition.

About the Author

Rudolf J. Freund, Ph.D. and Ramon C. Littell, Ph.D.

Dr. Freund and Dr. Littell, both SAS users since 1972 and former SUGI chairmen, were closely associated with the Southern Regional Project that funded continued SAS development at North Carolina State University. In addition to their university positions, both authors publish widely in statistical and applied journals, consult in industry, and serve as Consulting Statisticians to their state Agricultural Experiment Stations. They are both fellows of the American Statistical Association.


Product Details

  • Paperback: 232 pages
  • Publisher: Sas Inst; 2nd edition (January 29, 1991)
  • Language: English
  • ISBN-10: 1555444296
  • ISBN-13: 978-1555444297
  • Product Dimensions: 7.8 x 5.1 x 1 inches
  • Shipping Weight: 1 pounds
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #3,633,289 in Books (See Top 100 in Books)

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Customer Reviews

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Average Customer Review
4.3 out of 5 stars (3 customer reviews)
 
 
 
 
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8 of 8 people found the following review helpful:
4.0 out of 5 stars Great entry level book, August 29, 2003
This book is great for anyone with some general knowledge on Linear Regression and limited experience with SAS. The book does an excellent job explaining the SAS output (which is not always very intuitive).
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4.0 out of 5 stars Excellent Review, December 1, 2009
This book contains an excellent review of most sas procedures related to regression. Some advanced topics are covered too.
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0 of 6 people found the following review helpful:
5.0 out of 5 stars It's very useful, November 5, 2006
Do you wanna learn using Sas and regression? It's a very good book to start. It also include some mathmetical equation imply process. So do not be afraid of the math things. I like this book.
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Inside This Book (learn more)
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First Sentence:
Multiple linear regression is a means to express the idea that a response variable, y, varies with a set of independent variables x1, x2, . . . , xm. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
wings cap rooms, proc loess, fish growth data, airline cost data, proc reg data, proc rsreg, model with several independent variables, unknown knots, proc nlin, exact collinearity, proc autoreg, line printer plots, response surface plots, ods output, principal component variables, proc logistic, proc gplot, detecting multicollinearity, uncorrected total, proc iml, optimum subsets, plot statement, proc plot, model statement, heterogeneous variances
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Procedure Model, Estimate Error, Mean Source, Squares Square, Adj R-Sq, Coeff Var, Dependent Mean, Parameter Estimates Parameter Standard Variable, Creating Data, Special Applications of Linear Models, User's Guide, Itl Intercept, Multiplicative Models, Predicted Residual, Squares Mean Square, Barbados Data, Dep Var, Three-Factor Response Surface Experiment, Approximate Correlation Matrix, Different Set of Data, Fitting Splines, Further Examination of Model Parameters, Observations Missing, Observations Read, Output Added
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