Drawing upon more than 30 years of experience in working with
statistics, Dr. Richard J. Harris has updated "A Primer of
Multivariate Statistics" to provide a model of balance between
how-to and why. This classic text covers multivariate techniques
with a taste of latent variable approaches. Throughout the book
there is a focus on the importance of describing and testing one's
interpretations of the emergent variables that are produced by
multivariate analysis.
This edition retains its conversational writing style while
focusing on classical techniques. The book gives the reader a feel
for why one should consider diving into more detailed treatments of
computer-modeling and latent-variable techniques, such as
non-recursive path analysis, confirmatory factor analysis, and
hierarchical linear modeling. Throughout the book there is a focus
on the importance of describing and testing one's interpretations
of the emergent variables that are produced by multivariate
analysis.
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