{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

10 Bayes HW3 Exam

# 10 Bayes HW3 Exam - Example 2 Your birthday is coming up...

This preview shows pages 1–8. Sign up to view the full content.

1/5/10 Example 2 Your birthday is coming up, and you are afraid that your wife might be planning a surprise party for you. In the past she has thrown you a surprise party on 10% of your birthdays. However, you know that if she is going to throw a party, there is an 80% she won’t make eye contact with you the day before. If she is not going to throw a party, there is only a 30% chance of no eye contact.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
1/5/10 Probability Tree for Ex.2 P(S) = .1 P(S’) = .9 P(Ec| S’) =.7 P(Ec’| S’) =.3 P(Ec| S) =.2 P(Ec’| S) =.8 Given P(Ec’|S) = 0.8 in the problem description. Since Ec and Ec‘ are exhaustive and by definition M.E., P(Ec’|S) = 1 - P(Ec|S)
1/5/10 Probability Tree for Ex.2 P(S) = .1 P(S’) = .9 P(Ec| S’) =.7 P(Ec’| S’) =.3 P(Ec| S) =.2 P(Ec’| S) =.8 P(Ec|S)P(S) = P(Ec ° S) P(Ec|S’)P(S’) = P(Ec ° S’) P(Ec’|S’)P(S’) = P(Ec’ ° S’) P(Ec’|S)P(S) = P(Ec ’° S) = .27 = .63 = .08 = .02 23 . 27 . 08 . 08 . ) ' ( ) ' | ' ( ) ( ) | ' ( ) ( ) | ' ( ) ' | ( = + = + = S P S E P S P S E P S P S E P E S P c c c c

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
1/5/10 Example 2 Answer the following questions: a) Two days before, what is your estimate of the probability of the surprise party? Answer: Since you have not yet “read her eyes” the day before the party, you must go on past data and guess that the chances are 10% b) The day before, she does not make ) ' ( ) ' | ' ( ) ( ) | ' ( ) ( ) | ' ( ) ' ( ) ( ) | ' ( ) ' | ( S P S E P S P S E P S P S E P E P S P S E P E S P c c c c c c + = =
1/5/10 Bayes Theorem P(Ec |S) = P(Ec p S)/P(S) P(S |Ec) = P(S ° Ec)/P(Ec)

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
1/5/10 Bayes Theorem P(Ec |S) = P(Ec p S)/P(S) P(S |Ec) = P(S ° Ec)/P(Ec) Therefor e P(Ec S S) = P(Ec | S)*P(S) P(S ± Ec) = P(S | Ec)*P(Ec)
1/5/10 Bayes Theorem P(Ec |S) = P(Ec p S)/P(S) P(S |Ec) = P(S ° Ec)/P(Ec) Therefor e P(Ec S S) = P(Ec | S)*P(S) P(S ± Ec) = P(S | Ec)*P(Ec) Therefor e P(Ec ( S) = P(S m Ec) P(Ec |S)*P(S) = P(S | Ec)*P(Ec)

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern