Use Nonparametric Capability
Analysis to evaluate the capability of your process without any assumptions about the
distribution of the data. Because parametric assumptions usually provide more accurate
estimates with less data, you usually choose a nonparametric analysis when no
distribution fits the data and no transformation makes a distribution fit the data.
Using this analysis, you can do the following:

- Determine whether the process is
capable of producing output that meets customer requirements.
- Evaluate the overall capability of the
process.

To perform the analysis, you must specify a lower or upper specification limit (or both)
to define your process requirements. The analysis evaluates the spread of the process
data in relation to the specification limits. When a process is capable, the process
spread is small relative to the specification spread. In addition, the analysis
estimates the proportion of product that does not meet specifications.

For example, a quality analyst wants to evaluate the capability of a bolt manufacturing
process. To satisfy customer requirements, the thread length of the bolts should be
within 0.1 mm of the target of 20 mm. The analyst uses a nonparametric capability
analysis to evaluate how well the process meets the specifications without any
assumptions about the distribution of the data.

## Where to find this analysis

To perform nonparametric capability analysis, choose .

## When to use an alternate analysis

Usually, parametric assumptions provide more accurate estimates of capability with
less data. To consider how well a parametric distribution fits your data sample, use
Automated Capability Analysis. If no
distribution fits the data, then the analysis uses the nonparametric method.