Product Description

This text takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques.

Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS and SPSS. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set – when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.

Product Details

• Amazon Sales Rank: #36587 in Books
• Published on: 2006-02-16
• Original language: English
• Binding: Paperback
• 1008 pages

From the Back Cover

Using Multivariate Statistics provides advanced students with a timely and comprehensive introduction to today’s most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher level mathematics.

This long-awaited revision reflects extensive updates throughout, especially in the areas of Data Screening (Chapter 4), Multiple Regression (Chapter 5), and Logistic Regression (Chapter 12). A brand new chapter (Chapter 15) on Multilevel Linear Modeling explains techniques for dealing with hierarchical data sets. Also included are syntax and output for accomplishing many analyses through the most recent releases of SAS and SPSS.

As in past editions, each technique chapter:

• discusses tests for assumptions of analysis (and procedures for dealing with their violation)
• presents a small example, hand-worked for the most basic analysis
• describes varieties of analysis
• discusses important issues (such as effect size)
• provides an example with a real data set from tests of assumptions to write-up of a results section
• compares features of relevant programs

About the Author
Barbara G. Tabachnick, California State University, Northridge. Linda S. Fidell, California State University, Northridge.

Customer Reviews

A practical and valuable to your statistic library
This statistics book is a handy and easy to navigate guide to both basic and advanced methods of multivariate analysis. It is written in a very accessible style, and the SPSS example printouts provide clear and practical guidance for data analysis. In summary, a good blend of theory and hands on examples, and an excellent text for those studying at a postgraduate level as well a more advanced text for undergraduates.

The blue slope of statistics books
This book is a must for those who are about to write up the results section of their thesis related to the social sciences. Tabachnick and Fidell explain the statistical analyses from clean up to advanced structural equation modelling with relevant SPSS, SYSTAT, and SAS syntax commands to execute the analyses. These syntax files are particularly handy when T & F recommend tests that are not part of the basic knowledge researchers may have about these packages. However, if only basic knowledge is exactly what is required and/or you are a beginner at stats, I would suggest Andy Field's Discovering Statistics (SPSS only) instead. Field himself uses T & B as a resource, which highlights the totem-pole order here. Tabachnick and Fidell's book is an excellent source of reference with detailed information on each type of analysis, but not for the faint-hearted.

my favourite companion
T and F is a good comprehensive text for anyone who wants to gain a thorough understanding of advanced statistical techniques for social sciences. Not recommended as an intro text though, because it assumes a fairly firm bedrock of knowledge.