What inspired this Wish List Request?
Many JMP customers deal with test data (pass/fail) and often compare fail-rates (or yields) across categorical variables (ex. does Product A show a statistically different fail-rate from Product 
. They want to conveniently visualize those fail-rates and confidence intervals in an intuitive way. Currently this cannot be done with Fit Y by X or Graph Builder, and only done in Distribution. But Distribution is not intended to be used to compare a response versus a factor so it is not intuitive nor convenient.
(refer to this post on SE community)
Please describe the new or improved feature or solution you would like to see.
The improved feature would be options in Contingency and Graph Builder to include confidence interval for binomial responses and perform p-value calculations to determine if different groups have statistically different fail-rates. The new feature would look something like the graph on the right, whereas the left shows what Graph Builder currently can do which is not technically correct for a binomial response:
What would the value be to you and/or other users if this new feature is provided?
Engineers analyzing test data (many of these) would be able to use JMP to create intuitive visuals comparing fail-rates and product statistical tests to determine significance between categorical levels.
Is this an external customer request?
Yes, this feature has been requested by many companies including but not limited to Meta, Nvidia, Tesla, Rivian, Intel, AMD, Apple.
Is there a competitive software package that has this feature or solution that we should be aware of?
Competitive software such as Exensio (DataPower), Optimal+, Yield Explorer has this capability to do statistical tests across binomial responses
Will this impact a renewal, expansion, or adoption at a customer, and does this put an account at risk if we do not address this?
Likely no, but this feature is highly requested and makes JMP more intuitive and easier to use.
