ECON 2B03 Lecture Notes - Lecture 9: Cumulative Distribution Function, Thomas Bayes, Face Card

• School: McMaster University
• Department: Economics
• Course: ECON 2B03
• Professor: Jeff Racine

Document Summary

P ( a )=p ( a b )+p ( a b) P ( a b)=p( a )+p ( b) p ( a b ) P (b) p ( a b)=p ( a b ) P ( a ) p ( b a)=p( b a) P ( a b )= p ( a b) P (b a )= p ( b a ) The probability of drawing a heart (event b) is an unconditional probability p(heart) = p(b) = 13/52. The probability of drawing a face card (event a) given tht the card drawn was a heart (event b) is a conditional probability p(face card| heart) = p(a|b) = (3/52)/(13/52) = 3/13. You could apply the unconditional from joint probability rule, i. e. , P(face card) = all suits p (face card suits) = p(face card and heart) +p(face card and club)+p(face card and spade) + p(face card and diamond) A joint probability table shows frequencies or relative frequencies for joint events.