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Error Tolerance and Confidence Level An approximate error may
exist in displayed information. Error tolerance for a level of confidence is
calculated using the mean of the standard deviations and the mean of the
means. Error tolerance gives an indication of the stability of the
information. For example, if the error is 5% for a confidence level of
95%, then you can be 95% confident that the information has an error of
5% or less.
The Student's "T" distribution is used in these calculations because it
improves the accuracy for small samples. As the size of the sample increases,
the Student's "T" distribution approaches the normal distribution.
The following equation is used to calculate error tolerance:
Where:
O
Mean of the standard deviations.
m
t
Table entry in Student's "T" table for a given confidence level.
N
Number of traces in the measurement.
P
Mean of the means (i.e., mean sample).
m
Examples
Consider the following activity measurement report (generated with the
commands shown):
display trace depth 512
trace counting time
performance_measurement_initialize addr_ranges
performance_measurement_run 20
performance_measurement_end
!perf32 | more
Making Software Performance Measurements
To interpret activity measurement reports
267
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