Using Multivariate Statistics: International Edition

Tabachnick, Barbara G.

ISBN 10: 0205465250 / ISBN 13: 9780205465255

Editore: Pearson, 2005

Riguardo questo articolo

Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned.

Codice articolo wbs4087611271

Dati bibliografici

• Titolo: Using Multivariate Statistics: International Edition
• Editore: Pearson
• Data di pubblicazione: 2005
• Lingua: Inglese
• ISBN 10: 0205465250
• ISBN 13: 9780205465255
• Rilegatura: Brossura
• Edizione: quinta edizione o successive
• Condizione: Good
• Peso: 1330 grammi

Descrizione articolo

Riassunto

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.

Dalla quarta di copertina

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