Unless you want to “write a Shakespearean sonnet about Bayes’ rule”. Here’s what Claude sonnet (ahem) came up with:

"Bayes's Revelation"

  What knowledge held before new facts arrive,
  Our prior thoughts, though incomplete they be,
  Must yield and change as evidence does strive
  To shape posterior probability.

  Through multiplicative steps we find our way,
  As likelihood with prior beliefs combine,
  The normalizing constant holds its sway,
  While truth emerges, clearer line by line.

  O Reverend Bayes, thy theorem divine
  Shows how our minds should learn from what we see,
  Each observation helps our thoughts refine,
  Till posterior wisdom sets uncertainty free.

  In statistics' realm, this rule holds fast:
  Each present builds upon what's known from past.

  The sonnet weaves together the key components of Bayes' theorem - prior probability, likelihood, and how they combine to form the posterior probability. Would you like me to explain any of these statistical concepts in more detail?                

Although it would be an easier change now that Bard is Gemini…