Information Technology Reference
In-Depth Information
Chapter 2
Hypotheses: The Why of
Your Research
I
N THIS CHAPTER WE REVIEW HOW TO FORMULATE
a hypothesis that is
testable by statistical means, the appropriate use of the null hypothesis,
Neyman-Pearson theory, the two types of error, and the more general
theory of decisions and losses.
PRESCRIPTION
Statistical methods used for experimental design and analysis should be
viewed in their rightful role as merely a part, albeit an essential part, of
the decision-making procedure.
1. Set forth your objectives and the use you plan to make of your
research
before
you conduct a laboratory experiment, a clinical
trial, or a survey and
before
you analyze an existing set of data.
2. Formulate your hypothesis and all of the associated alternatives.
List possible experimental findings along with the conclusions
you would draw and the actions you would take if this or another
result should prove to be the case. Do all of these things
before
you complete a single data collection form and
before
you turn
on your computer.
WHAT IS A HYPOTHESIS?
A well-formulated hypothesis will be both quantifiable and testable—that
is, involve measurable quantities or refer to items that may be assigned to
mutually exclusive categories.
A well-formulated statistical hypothesis takes one of the following forms:
“Some measurable characteristic of a population takes one of a specific set
