Advanced and Multivariate Statistical Methods
Practical Application and Interpretation
Sixth Edition 2017



This text was written for use by students taking a multivariate statistics course as part of a
graduate degree program in which the course is viewed as a research tool. Examples of degree programs
for which this text would be appropriate include—but are not limited to—psychology, education, sociology,
criminal justice, social work, mass communication, and nursing. Although the text is not primarily
intended for students who are majoring in statistical or research methodologies, they could certainly
use it as a reference.
This text has three main purposes. The first purpose is to facilitate conceptual understanding of
multivariate statistical methods by limiting the technical nature of the discussion of those concepts and
focusing on their practical applications. The multivariate statistical methods covered in this text are:
 factorial analysis of variance (ANOVA),
 analysis of covariance (ANCOVA),
 multivariate analysis of variance (MANOVA),
 multivariate analysis of covariance (MANCOVA),
 multiple regression,
 path analysis,
 factor analysis,
 discriminant analysis, and
 logistic regression.
The second purpose is to provide students with the skills necessary to interpret research articles
that have employed multivariate statistical techniques. A critical component of graduate research projects
is a review of research literature. It is crucial for students to be able to understand not only what
multivariate statistical techniques were used in a particular research study, but also to appropriately
interpret the results of that study for the purposes of synthesizing the existing research as background
for their own study. The acquisition of these skills will benefit students not only during the time that
they are conducting their graduate research studies, but also long after that time as they review current
research as part of their professional career activities.
The third purpose of this text is to prepare graduate students to apply multivariate statistical
methods to the analysis of their own quantitative data or that of their institutions, such that they are
able to complete the following for each particular technique:

 understand the limitations of the technique,
 fulfill the basic assumptions of the technique,
 conduct the appropriate steps (including the selection of various options available through the
use of computer analysis software),
 interpret the results, and
 write the results in the appropriate research reporting format.





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