Information Technology Reference
In-Depth Information
Chapter 3
Collecting Data
GIGO Garbage in, garbage out.
“Fancy statistical methods will not rescue garbage data.”
Course notes of Raymond J. Carroll [2001].
T
HE VAST MAJORITY OF ERRORS IN STATISTICS—AND,
not incidentally, in
most human endeavors—arise from a reluctance (or even an inability) to
plan. Some demon (or demonic manager) seems to be urging us to cross
the street before we've had the opportunity to look both ways. Even on
those rare occasions when we do design an experiment, we seem more
obsessed with the mechanics than with the concepts that underlie it.
In this chapter we review the fundamental concepts of experimental
design, the determination of sample size, the assumptions that underlie
most statistical procedures, and the precautions necessary to ensure that
they are satisfied and that the data you collect will be representative of the
population as a whole. We do not intend to replace a text on experiment
or survey design, but to supplement it, providing examples and solutions
that are often neglected in courses on the subject.
PREPARATION
The first step in data collection is to have a clear, preferably written state-
ment of your objectives. In accordance with Chapter 1, you will have
defined the population or populations from which you intend to sample
and have identified the characteristics of these populations you wish to
investigate.
You developed one or more well-formulated hypotheses (the topic of
Chapter 2) and have some idea of the risks you will incur should your
analysis of the collected data prove to be erroneous. You will need to
