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Because data samples are random, it is unlikely that two samples from the same population will yield identical tolerance intervals. But, if you collect many samples, a certain percentage of the resulting tolerance intervals will contain the minimum proportion of the population that you specify.
The confidence level is the likelihood that the tolerance interval actually includes the minimum percentage. For example, an engineer wants to know the range within which 99% of the future product will fall, with 98% confidence. 98% is the confidence level for the tolerance interval.
| Confidence level | 98% |
|---|---|
| Percent of population in interval | 99% |
You can specify the confidence level for the analysis in the Options dialog box. Minitab displays the target confidence level in the Methods table. By default, the confidence level is 95%. For the nonparametric method, Minitab calculates the achieved confidence level. The achieved confidence level is the exact confidence level that Minitab calculates. The achieved confidence level is usually greater than or equal to the target confidence level, unless your sample size is too small.
The percent of population in the interval is the minimum percentage of the population that you want the tolerance interval to include. For example, an engineer wants to know the range that will include 99% of the future product, with 98% confidence. 99% is the percent of population in the tolerance interval.
| Confidence level | 98% |
|---|---|
| Percent of population in interval | 99% |
The sample size (N) is the total number of observations in the sample. In this data, the sample size is 400.
| Variable | N | Mean | StDev |
|---|---|---|---|
| C1 | 400 | 0.604 | 3.671 |
The mean summarizes the sample values with a single value that represents the center of the data. The mean is the average of the data, which is the sum of all the observations divided by the number of observations.
In this data, the mean is 0.604.
| Variable | N | Mean | StDev |
|---|---|---|---|
| C1 | 400 | 0.604 | 3.671 |
The standard deviation is the most common measure of dispersion, or how spread out the data are from the mean.
A larger standard deviation indicates that your data are spread more widely around the mean and will result in a wider tolerance interval. A smaller standard deviation indicates that your data are distributed more closely around the mean and will result in a narrower tolerance interval.
In this data, the standard deviation is 3.671.
| Variable | N | Mean | StDev |
|---|---|---|---|
| C1 | 400 | 0.604 | 3.671 |
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