Specify the default sigma (σ) tolerance for capability statistics, and the method for calculating nonnormal capability statistics. The changes you make to the defaults remain until you change them again, even after you exit Minitab.
- Use tolerance of K x σ for capability statistics K=
- To calculate the capability statistics using an interval other than 6 standard deviations wide (3 on either side of the process mean), enter the number here.
- Nonnormal Capability Statistics
- Z-score method: Calculate capability statistics using the Z-score method (also known as the Minitab method).
- ISO method: Calculate capability statistics using the ISO method.
Specify the statistics to display.
- Capability stats (Cp, Pp): Display capability statistics.
- Benchmark Z's (sigma level): Display benchmark Z statistics.
- CCpk: Display CCpk statistics.
- Parts per
million: Display the values in parts per million (PPM).
- Percents: Display the values as percentages.
- Include confidence
- Select to display confidence intervals for the capability indices.
- Enter a confidence level between 0 and 100. Usually, a confidence level of 95% works well. A 95% confidence level indicates that if you took 100 random samples from the process, you could expect approximately 95 of the samples to produce confidence intervals that contain the actual value of the capability index for the process (if all the process data could be collected and analyzed).
- For a given set of data, a lower confidence level produces a narrower confidence interval, and a higher confidence level produces a wider confidence interval. The width of the interval also tends to decrease with larger sample sizes. Therefore, you may want to use a confidence level other than 95%, depending on your sample size, as follows:
- If your sample size is small, a 95% confidence interval may be too wide to be useful. Using a lower confidence level, such as 90%, will produce a narrower interval. However, the likelihood that the interval contains the capability index for the process decreases.
- If your sample size is large, you may want to consider using a higher confidence level, such as 99%. With a large sample, a 99% confidence level may still produce a reasonably narrow interval while increasing the likelihood that the interval contains the capability index for the process.
- Select the type of confidence interval or bound that you want to display:
- One-sided: Displays lower confidence bounds for capability indices and upper confidence bounds for PPM or % out-of-specification limits. Use one-sided confidence bounds for the following:
- To be more confident that a capability index is greater than a required value. For example, to be more confident that Cp is greater than 1.33.
- To be more confident that a PPM or % out-of-specification limits is less than a required value. For example, to be more confident that PPM Total out-of-specification is less than 100.
- Two-sided: Display a confidence interval that has both a lower and an upper confidence bound.