7.
Product and Process Comparisons
7.1.
Introduction
7.1.2.

What assumptions are typically made?


Validity of tests

The validity of the tests described in this chapter depend on the
following assumptions:
 The data come from a single process that can be represented
by a single statistical distribution.
 The distribution is a normal distribution.
 The data are uncorrelated over time.


An easy method for checking the assumption of a single
normal distribution is to construct a
histogram
of the data.

Clarification

The tests described in this chapter depend on the assumption of
normality, and the data should be examined for departures from
normality before the tests are applied. However, the tests are
robust to small departures from normality; i.e., they work fairly
well as long as the data are bellshaped and the tails are not
heavy. Quantitative methods for
checking the normality assumption are discussed in the next
section.


Another graphical method for testing the normality assumption
is the normal
probability plot.


A graphical method for testing for correlation among
measurements is a
timelag plot.
Correlation may not be a problem if measurements are
properly structured over time. Correlation problems often
occur when measurements are made close together in time.
