Expert insights from Professor William Q. Meeker, part 3

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In the third installment of the series, this post highlights portions of JMP Chief Data Scientist Chris Gotwalt’s interview with award-winning and widely published reliability expert, William Q. Meeker, Professor of Statistics and Distinguished Professor of Liberal Arts at Iowa State University. The first post touched on “proactive reliability” and how machine learning, IoT, and Industry 4.0 have implications for maintenance and improved reliability. The second post explored overlapping disciplines and foundational contributions of statistics, as well as the evolution of statistics education.

The interview was paired with the plenary talk Bill recorded for the 2021 Discovery Summit Japan. This blog series features sections of Chris’ interview to shine light on Bill’s many contributions to statistics, as well as two recent books he has co-authored: Achieving Product Reliability: A Key to Business Success, with Necip Doganaksoy and Gerald J. Hahn; and the second edition of Statistical Methods for Reliability Data, which Bill co-authored with Luis A. Escobar and Francis G. Pascual. You can download the first chapter of Achieving Product Reliability.  

For years, developers at JMP have happily engaged with Bill to add new methods for reliability analysis into JMP software. It has been very rewarding to have this collaborative relationship with Bill to incorporate new and better methods to enable better product reliability.

In the first clip, Bill talks about the growing importance of Bayesian methods and the scenarios in which a Bayesian approach is warranted. Bill offers fascinating insights into the thoughtful judgment that comes into play when applying priors.

Next, Bill discusses Bayesian methods gaining more exposure and becoming computationally more accessible.

In the next post, Bill reveals his motivation for writing the book on statistical intervals, as well as an interesting exchange he had with W. Edwards Deming.