Count Bayesie Speaks Truth
September 10, 2020
Navigate to “Why Bayesian Stats Needs More Monte Carlo Methods.” Each time I read an informed write up about the 18th century Presbyterian minister who could do some math, I think about a fellow who once aspired to be the Robert Maxwell of content management. Noble objective is it not?
That person grew apoplectic when I explained how Autonomy in the early 1990s was making use of mathematical procedures crafted in the 18th century. I wish I have made a TikTok video of his comical attempt to explain that a human or software system should not under any circumstances inject a data point that was speculative.
Well, my little innumeric content management person, get used to Bayes. Plus there’s another method at which you can rage and bay. Yep, Monte Carlo. If you were horrified by the good Reverend’s idea, wait until you did into Monte Carlo. Strapping these two stastical stallions to the buggy called predictive analytics is commonplace.
The write up closes poetically, which may be more in line with the fuzzy wuzzy discipline of content management:
It may be tempting to blame the complexity of the details of Bayesian methods, but it’s important to realize that when we are taught the beauty of calculus and analytical methods we are often limited to a relatively small set of problems that map well to the solutions of calc 101. When trying to solve real world problems mathematically complex problems pop up everywhere and analytical solutions either escape or fail us.
Net net: Use what matches the problem. Also, understand the methods. Key word: Understand.
Stephen E Arnold, September 10, 2020
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One Response to “Count Bayesie Speaks Truth”
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Great as an idea-unfortunately won’t work out in reality, oh well..