
When it’s Not Normal: How to Choose from a Library of Distributions
When trying to fit a probability distribution to quantitative results, sometimes the normal probability doesn’t fit. Minitab has a wealth of distributions to pick from. Do you just pick whichever one Minitab tells you fits the best? Maybe not. Just because the distribution fits your data doesn’t mean it’s a good one to use. We review my top 3 distributions for product testing and some other ones that come up but may not be appropriate to use.
We’ll also share what you need to think about when picking a distribution:
- think about your purpose of test
- consider your failure mode and how you’re expecting your product to perform – does the typical use case of a distribution fit?
- when you have options, the simpler the distribution the better (i.e. choose a 2-parameter over a 3-parameter)
We have identified a failure of our design. It’s a complicated failure that has multiple potential root causes, and some that are conditional. Is there a tool that can capture it all and help us prioritize our reactions to get rid of this problem? Yes, there is: Fault Tree Analysis!
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