A confidence interval covers a population parameter with a
stated confidence, that is, a certain proportion of the time.
There is also a way to cover a fixed proportion of the
population with a stated confidence. Such an interval is called
a tolerance interval. Statistical tolerance intervals are limits
in which we expect a stated proportion of the individual values
of the population to lie. For a sample mean (X mean) and sample
standard deviation (s), the general formula for a tolerance
interval is: The value of k is based on the sample size (n) and
the confidence level (1-α). The k factor can be obtained from
the appropriate table contained in ISO-16269-6 Statistical
Interpretation of Data reference or calculated by statistical
software. Revisiting the data from Table 1, the tolerance
interval calculations for a 95% confidence and 95% coverage can
be found in Table 2. Tolerance interval calculations for 95%
confidence and 95% coverage The tolerance interval means we are
95% confident that 95% of the individ