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Unformatted text preview: ge deviation (ppt) in addition to the standard
deviation in all experiments.
Analysis of Poor Data: Q-test
Sometimes a single piece of data is inconsistent with other data. You need a
method to determine, or test, if the data in question is so poor that it should be
excluded from your calculations. Many tests have been developed for this
purpose. One of the most common is what is known as the Q test. To determine
if a data should be discarded by this test you first need to calculate the difference
of the data in question from the data closest in value (this is called the "gap").
Next, you calculate the magnitude of the total spread of the data by calculating the
difference between the data in question and the data furthest away in value (this is
called the "range"). You will then calculate the QData, given by
QData = range
and compare the value to that given in the table below. The values in the table
below are given for the 90% confidence level. If the QData is greater than...
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- Spring '07