n n n n n
248 n Interpreting the CMMI
There are automated tools that can support building and displaying these
charts. But remember, a tool does not do the thinking for you. It is up to you
to collect the data correctly, to collect the correct data, and to interpret the
results correctly.
Another suggested reason for using the XmR chart: Do you understand the
terms binomial probability and Poisson probability? Do you know how to verify these
probability models? If the answer is no or ???What kinda language are you talking????
then stick with the XmR. Life is complicated enough.
The task we need to undertake is to figure out how to tell the difference between
noise and signals in our process data. Properly generated control charts, specifi-
cally the XmR chart, can help us in this task. Past data (historical data) are critical
for generating accurate control charts and for correct SPC analyses. To determine
whether the results found are normal noise or true signals, comparisons of past
data limits must be made and moving ranges determined.
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