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Produktbeschreibungen
Pressestimmen
"...an excellent textbook...I would certainly recommend it for educational as well as for applied research purposes" (Statistical Methods in Medical Research, No.13, 2004) "I highly recommend the third edition of Introduction to Linear Regression Analysis to practitioners, students, and teachers of regression analysis." (Technometrics, May 2002) "an excellent text" (Zentrablatt Math, Vol. 980, No. 05, 2002) "...a very good book..." (The American Statistician, Vol. 57, No. 1, February 2003)
Kurzbeschreibung
Die Regressionsanalyse ist eines der am häufigsten verwendeten statistischen Verfahren zur Untersuchung von multiplen Daten. Dieses Lehrbuch bietet eine Einführung in die Grundlagen der linearen Regressionsanalyse. Behandelt werden die Standardthemen sowie einige neuere, unkonventionellere Themen. Der Schwerpunkt liegt auf der Verbindung von Theorie und praktischer Anwendung. Diese 3. Auflage wurde komplett überarbeitet und erweitert.
Lineare Regressionsverfahren gehören zum Rüstzeug jedes Statistikers und Ingenieurs. Einen Überblick über den aktuellsten Stand der Forschung verschaffen Sie sich mit diesem Buch.
Lineare Regressionsverfahren gehören zum Rüstzeug jedes Statistikers und Ingenieurs. Einen Überblick über den aktuellsten Stand der Forschung verschaffen Sie sich mit diesem Buch.
In diesem Buch
(Mehr dazu)
Einleitungssatz
Regression analysis is a statistical technique for investigating and modeling the relationship between variables. Lesen Sie die erste Seite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
Regression analysis is a statistical technique for investigating and modeling the relationship between variables. Lesen Sie die erste Seite
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
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Kundenrezensionen
Die hilfreichsten Kundenrezensionen
Format:Gebundene Ausgabe
This is one of the best books on the market for a course on linear regression analysis. It contains everything from the basic least squares equations to problems of multicollinearity, and a section on non-linear regression is also thrown in for good measure. Not a cheap book (Wiley would do well to consider inexpensive paperback editions for non-plutocrats)but highly recommended nevertheless. The book contains many applications to real-life problems and questions are included at the ends of the chapters, making this a valuable textbook for a very wide range of students.
Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)
Amazon.com:
11 Rezensionen
18 von 21 Kunden fanden die folgende Rezension hilfreich
Excellent introduction to linear regression
12. Januar 2005
Format:Gebundene Ausgabe
If you have a desire or need to develop regression models, whether for prediction or classification, this is a great place to start climbing the learning curve. The book covers all the essentials, such as how to fit a model to a set of data, how to evaluate the quality of the fit, and how to detect influential data points. It also does a good job with some of the issues involved in fitting a regression (most notably colinearity, overfitting, outliers, and deviations from normality) and discusses ridge regression, principal components regression, and other so-called "robust" methods for dealing with such issues. Even if you plan to use nonlinear modelling techniques like polynomial regression or feed-forward neural networks, this book is worth reading: many of the same issues that are involved when developing linear regression models arise in the context of nonlinear models. I use multivariate polynomial regression models for pricing options, and cite this book in my own recent work on that subject--"Advanced Option Pricing Models" (McGraw Hill, Feb 2005).
Jeffrey Owen Katz, Ph.D.
Author (with Donna L. McCormick) of "The Encyclopedia of Trading Strategies" (McGraw Hill, 2000).
Jeffrey Owen Katz, Ph.D.
Author (with Donna L. McCormick) of "The Encyclopedia of Trading Strategies" (McGraw Hill, 2000).
4 von 4 Kunden fanden die folgende Rezension hilfreich
For Self Study Get An Earlier Edition
28. Januar 2010
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
I have access to this, the third edition and the latest, the fourth edition, through my company's library. There is really no material difference in the content and I was able to save about 80% of the purchase price by buying a used copy of the third edition, vs. new copy of fourth edition.
Wonderful book for self study. You will benefit most if you have a good background in probability theory and linear algebra and want to understand the details and language of linear regression. Even without that background chapters one through three will teach you more than you will ever learn in most survey courses in statistics. To fully appreciate the whole book I think you need a one semester course in linear algebra and one or two semesters of probability theory.
Wonderful book for self study. You will benefit most if you have a good background in probability theory and linear algebra and want to understand the details and language of linear regression. Even without that background chapters one through three will teach you more than you will ever learn in most survey courses in statistics. To fully appreciate the whole book I think you need a one semester course in linear algebra and one or two semesters of probability theory.
3 von 3 Kunden fanden die folgende Rezension hilfreich
Wiley needs a proofreader fantastically
15. Dezember 2010
Format:Gebundene Ausgabe
This was used as the textbook in a course in Linear Regression
Analysis that I recently attended as an auditor. I'm a mathematician,
not a statistician, so much of the material, and the authors' ways of
looking at it, were not familiar to me. My statistician colleagues
assure me that the techniques in the book are correct, useful, and
mostly up to date. And I believe them.
Alas, the book is poorly edited, and in just the few chapters we
covered, I found a score of errors, including misstated formulas,
misplaced graphics, multiplication where there should be division, and
even some numerical errors. If you, as an instructor, decide to adopt
this book for your course, be prepared to do a lot of proofreading
(the publisher apparently didn't bother) and to distribute textbook
corrections to your students. Also note that this book, like so many
Wiley textbooks, is overpriced.
Analysis that I recently attended as an auditor. I'm a mathematician,
not a statistician, so much of the material, and the authors' ways of
looking at it, were not familiar to me. My statistician colleagues
assure me that the techniques in the book are correct, useful, and
mostly up to date. And I believe them.
Alas, the book is poorly edited, and in just the few chapters we
covered, I found a score of errors, including misstated formulas,
misplaced graphics, multiplication where there should be division, and
even some numerical errors. If you, as an instructor, decide to adopt
this book for your course, be prepared to do a lot of proofreading
(the publisher apparently didn't bother) and to distribute textbook
corrections to your students. Also note that this book, like so many
Wiley textbooks, is overpriced.
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