Contents - Index

Confidence Level

Confidence levels are associated with normal tolerance intervals, variables sampling plans, tests of fit, tests of group differences and tests if there was a shift over time (order).  The confidence statement can be thought of as representing the probability the statement or conclusion is correct.  By default, confidence levels of 95% are used.  You can adjust the confidence level used for normal tolerance intervals and variables sampling plans using the Analysis Options dialog box or Tolerance Interval Options dialog box. 

For tests of fit (normality tests), the confidence level is based on the significant level, alpha-level or p-value.  The p-value is the probability that the data or one more extreme than it would have been generated had the data come from the selected distribution.  A p-value of 0.05 would indicate that the chance of the observed data is low, 1 in 20, due to variation alone.  This is good evidence that the data is not from the selected distribution.  A p-value of 0.5 would indicate that there is a 50-50 chance of the something as extreme as the observed data assuming the selected distribution.  This is consistent with the selected distribution.  The smaller the p-value, the greater the evidence that the data did not come from the selected distribution.

For tests of fit and other tests, the confidence level is calculated from the p-value as 100*(1 - p-value).  Therefore:

Confidence Level p-value

          99%    0.01
          95%    0.05
          90%    0.1
          80%    0.2
          50%    0.5