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Lesson8

# Lesson8 - MU 1 1.430 — Lesson 0 Bayes Theorem Prior and...

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Unformatted text preview: MU 1 1.430 — Lesson 0 Bayes Theorem Prior and Posterior (Revised) Probabilities: ‘ V APPLY ASHE/Llde- \ 7 Fm“ -> Ne“, eavﬁe'j‘ ...-, 6-. (LAM/5:7 PM“ ' I “m rm «asz PM Comp/+41% [LACFHVM PAM) th ‘ e9 SuPPL—uﬁfu: 14‘ 4 '41 o 49/. MAM/41 PM!) 1.4? ‘> Pam/4 3ft men 9:. {904172.55 Prams Development of Bayes Theorem: Need «MFG ‘ Frau/l4 A, 927. Mi Gaga A“ 012/6 MLQAO (9/ - AL 2‘ 20mm «201 ' a” MC“- PCé/Mzwr ‘ 7 Nels)? Woe/6) A Example Problem: A city has a professional basketball team playing at home and a professional hockey team playing away on the same night. From past experience, the probability of the basketball team winning a home game has been 0.641 and the probability of the hockey team winning an away game 0.462. Historically, when both teams play on the same night, the chance that the lead story in the next morning’s sport section would be about the basketball team has been 60% and about the hockey team 40%. If the morning edition of the paper carries the lead story titled “We Winl”, what is the probability it is about the basketball team? 9(Aig)2 Pchw/Av) ‘ waﬂmj 9/41 p6/h.) Pm; Mam; r Pom Fae/m} WWW ,PﬂM/d P<ﬁ #01 pC82€[email protected]/g) I _ W P66) 1.» , Q My War/1127‘ Pam/w) COLD/1) M30 p(5’/w)" M p( WM?- (é-W CéJZ-mjb (.cf/(.t/£7—/ A H;?lY§MH ...
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