Best Practices in Relaibility Data Analysis Background
Best Practices in Reliability Data Analysis

Probability Plots in Life Distribution

How can you accurately predict the time-to-failure for your components and products? In this presentation, Bill Meeker, PhD, Professor of Statistics at Iowa State University, provides an overview of one of the most widely-used statistical tools for analyzing reliability data: probability plots. Using an example of a fatigue test on an alloy, Dr. Meeker will help you gain a better understanding of:

  • The primary purposes of probability plots.
  • How to assess the adequacy of different probability plotting scales including normal, Weibull and lognormal.
  • How to fit a distribution to the data and extrapolate failure rates into the future using maximum likelihood estimation.
See these techniques in action!

To learn more and see how probability plots can be implemented in JMP, register below.

Probability Plots in Life Distribution in JMP

Hands-on Case Study

Join JMP product manager Leo Wright as he brings Dr. Meeker’s examples to life using JMP software.

In this video, Leo Wright provides a step-by-step demonstration of how to create probability plots and perform life distribution analysis in JMP using the alloy fatigue test example introduced by Dr. Meeker. 

To explore these capabilities for yourself, download JMP for free for 30 days.

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