Evidence

The likelihood ratio term $\$\frac{P(B | A)}{P(B|\neg A)}$ from Bayes' theorem is greater than 1 if the event B is evidence of the theory A, and less than 1 if the event is evidence against the theory.

The likelihood ratio term $P(B|A)P(B|¬A)$ from Bayes' theorem is greater than 1 if the event B is evidence of the theory A, and less than 1 if the event is evidence against the theory.

See also

• Rational evidence, Evidence of absence, Extraordinary evidence
• Filtered evidence
• Generalization from fictional evidence
• Conservation of expected evidence

See also

• Rational evidence, Evidence of absence, Extraordinary evidence
• Filtered evidence
• Generalization from fictional evidence
• Conservation of expected evidence

Posts by Others:

• theory and the symmetry of updating beliefs (by Academian)

Posts by Eliezer Yudkowsky:

• What is Evidence? by Eliezer Yudkowsky
• How Much Evidence Does It Take? by Eliezer Yudkowsky
• Scientific Evidence, Legal Evidence, Rational Evidence by Eliezer Yudkowsky
• The Lens That Sees Its Flaws by Eliezer_Yudkowsky
• No One Can Exempt You From Rationality's Laws by Eliezer_Yudkowsky
• That Alien Message by Eliezer_Yudkowsky

Posts by Eliezer Yudkowsky:

Posts by Others:

• Information theory and the symmetry of updating beliefs (by Academian)by Academian

The likelihood ratio term $\frac{P($P(B| A)}{P(B|\neg A)}A)P(B|¬A)$ from Bayes' theorem is greater than 1 if the event B is evidence of the theory A, and less than 1 if the event is evidence against the theory.

• Information theory and the symmetry of updating beliefs (by Academian)