Home > Using multivariate statistics.

Tabachnick, Barbara G and Fidell, Linda S (2007) Using multivariate statistics. London: Pearson .


After the Introduction Chapter, the second Chapter gives a guide to the multivariate techniques that are covered in this book and places them in context with the more familiare univeriate and bivariate statistics where possible. Included in this chapter is a flow chart that organizes statistical techniques on the basis of the major research questions asked.
Chapter three provides a brief review of univariate and bivariate statistical techniques for those who are interested. Chapter four deals with the assumptions an limitations of mulitvariate statistical methods. Assessment and violation of assumptions are discussed, along with alternatives for dealing with violations when they occur. This chapter is also meant to be referred to often, and the reader ist guided back to it frequently in Chapters five through sixteen an eighteen (online).
Chapters five through sixteen and eighteen (online) cover specific multivariate techniques. They include descriptive, conceptual sections as well as a guided tour through a real-world data set for which the analysis is apporopriate. The tour includes an example of a Results section describing the outcome of the statistical analysis apporopriate for submissions to a professional journal. Each technique chapter includes a comparision of cumputer programs.
Chapter seventeen is an attempt to integrate univariate, bivariate, and multivariate statistics through the multivariate general linear model. The common elements underlying all the techniques are emphasized, rather than the differences among them. This Chapter is ment to pull together the material in the remainder of the book with a conceptual rather than pragmatic emphasis.
Item Type:Book
Date:2007
Call No:RQ8
Pages:980 p.
Publisher:Pearson
Place of Publication:London
ISBN:9780205465255
EndNote:View
Accession Number:HRB 5321 (Available)
Related URLs:
Subjects:R Research
R Research > Type of research study > Empirical study > Quantitative study (statistical data)

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