Improving public understanding of probability and risk with special emphasis on its application to the law. Why Bayes theorem and Bayesian networks are needed
Friday 17 January 2020
Understanding Bayes theorem
As part of my presentation at the Wolfson Institute of Preventative Medicine today I got some audience participation using the mentimeter tool. One of the things I did was to test the participants' understanding of Bayes before and after the seminar. I posed this question*:
The results were very interesting. Before the seminar the 'average' probability answer was 76% (but note the variation in the distribution)
After, the average was 9.4%
The correct answer is just below 0.5%:
*Based on example from: Neapolitan, Richard, Xia Jiang, Daniela P. Ladner, and Bruce Kaplan. 2016. “A Primer on Bayesian Decision Analysis With an Application to a Kidney Transplant Decision.” Transplantation 100 (3): 489–96.
No comments:
Post a Comment