Keep Calm and Bayes On
Intuitively Building Bayesian Reasoning for Clinical Medicine
The Bayes Formula
P(H|E) = P(E|H) × P(H) / P(E)
What the symbols mean:
P(H|E)
Posterior Probability
"Probability of Hypothesis given Evidence"
What we want to know
P(E|H)
Likelihood
"Probability of Evidence given Hypothesis"
How likely is this test result if they have the condition?
P(H)
Prior Probability
"Initial probability of Hypothesis"
Base rate or initial belief
P(E)
Evidence Probability
"Total probability of seeing this Evidence"
Normalizing factor
In plain English:
"The probability of having a condition after a positive test equals:
- • How common the condition is (prior)
- • Times how good the test is (likelihood)
- • Divided by how often we see positive tests overall"
🔑 Key Insight:
The "|" symbol means "given that" or "if we know"
Learning Objectives
- ✓Build intuition for Bayesian reasoning through everyday examples
- ✓Visualize how evidence updates beliefs
- ✓Apply Bayes theorem to clinical genetics scenarios
- ✓Master calculations with interactive tools
How This Lesson Works
- 1.Start with intuitive phone spam example
- 2.Visualize probability updates with billiard balls
- 3.Connect to ACMG variant interpretation
- 4.Practice with clinical scenarios
🎯 Activity: Match the Notation
Click any item on either side, then click its match on the other side. You can start from either column!
Probability Notations
What They Mean
💡 Remember:
The order matters! P(A|B) ≠ P(B|A)
The "|" symbol means "given that" or "if we know"