SPSS 15.0 Statistical Procedures Companion | 
 enlarge | Author: Marija Norusis
Publisher: Prentice Hall
Category: Book
List Price: $64.00
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Sales Rank: 367145
Media: Paperback
Edition: 1
Number Of Items: 1
Pages: 632
Shipping Weight (lbs): 2.1
Dimensions (in): 8.8 x 7.3 x 1
ISBN: 0131594176
Dewey Decimal Number: 519
EAN: 9780131594173
ASIN: 0131594176
Publication Date: December 24, 2006
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Product Description
A statistical procedure is not like a sausage: you want to know its contents; you want to know the types of questions it can be used to answer and the types of data for which it is appropriate. The goal of the SPSS 15.0 Advanced Statistical Procedures Companion is to provide you with background information and examples for statistical procedures in the SPSS Advanced and Regression Models modules. It aims to make it less likely that you will succumb to the siren song of melodic statistical procedure names and unleashes a disastrous assault on a mutely suffering data file.
For additional information, go to This site offers a detailed Table of Contents, features, examples included in the book, and a sample chapter for download.
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| Customer Reviews:
advanced data analysis August 3, 2007
1 out of 1 found this review helpful
Norusis starts off the book with a gentle introduction to SPSS 15. Going briefly into an overview of what the software makes available as analysis tools to you, via a GUI. Even at this level, if you have a good statistics background, the text shows a lot of procedures quickly accessible. Take the General Linear Model. SPSS offers 3 types - univariate, multivariate and repeated measures. While the correlation can be found for the bivariate and partial cases.
But it may be the regression facilities that you'll find most useful. Linear regression is available; of course! This is what all the elementary statistics texts teach. But Norusis describes more advanced regression routines. For binary logistic, or ordinal regression.
The book deliberately is not a comprehensive manual on SPSS. In general, the various screen captures, especially of the menus, show more options than are explained in the text. What Norusis has done is use enough of these to explain how to analyse a data set. You should treat the book primarily as a course in advanced data sifting. And only secondarily as an SPSS enabler. Granted, if you are already experienced in analysis, the latter reason may then be the main motivation for using the book.
There are no formal problem sets, per se, in the book. But the text does use data sets in its CD. Chapters typically end in exercises on employing SPSS to crunch those data sets.
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