Conventional statistical methods have a very serious flaw. They
routinely miss differences among groups or associations among
variables that are detected by more modern techniques, even under
very small departures from normality. Hundreds of journal articles
have described the reasons standard techniques can be
unsatisfactory, but simple, intuitive explanations are generally
unavailable. Situations arise where even highly nonsignificant
results become significant when analyzed with more modern
methods.
Without assuming the reader has any prior training in
statistics, Part I of this book describes basic statistical
principles from a point of view that makes their shortcomings
intuitive and easy to understand. The emphasis is on verbal and
graphical descriptions of concepts. Part II describes modern
methods that address the problems covered in Part I. Using data
from actual studies, many examples are included to illustrate the
practical problems with conventional procedures and how more modern
methods can make a substantial difference in the conclusions
reached in many areas of statistical research.
The second edition of this book includes a number of advances
and insights that have occurred since the first edition appeared.
Included are new results relevant to medians, regression, measures
of association, strategies for comparing dependent groups, methods
for dealing with heteroscedasticity, and measures of effect
size.
General
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