9780256070682-0256070687-Applied Linear Regression Models

Applied Linear Regression Models

ISBN-13: 9780256070682
ISBN-10: 0256070687
Edition: Subsequent
Author: Michael H. Kutner, William Wasserman, John Neter
Publication date: 1989
Publisher: Richard d Irwin
Format: Hardcover 688 pages
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Book details

ISBN-13: 9780256070682
ISBN-10: 0256070687
Edition: Subsequent
Author: Michael H. Kutner, William Wasserman, John Neter
Publication date: 1989
Publisher: Richard d Irwin
Format: Hardcover 688 pages

Summary

Applied Linear Regression Models (ISBN-13: 9780256070682 and ISBN-10: 0256070687), written by authors Michael H. Kutner, William Wasserman, John Neter, was published by Richard d Irwin in 1989. With an overall rating of 4.1 stars, it's a notable title among other books. You can easily purchase or rent Applied Linear Regression Models (Hardcover) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.56.

Description

"Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

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