Practice Problems & Exam info
Table of Contents
1. Example Again
P(Fails in 5 | exceeded 10)
= P(Fails in 5 n exceeds 10)/P(exceeds 10)
= P(fails in 15 n exceeds 10) / 1-P(doesnt exceed 10)
Side: P(failing in 15) = P(fails in 15 n exceeds 10) + P(fails in 15 n not exceed 10)
P(fails in 15 n exceeds 10) = P(failing in 15) - P(failing in 15 n not exceed 10)
Answer: P(fails in 15) - P(fails in 10)/1 - P(fails in 10)
2. Challenge Problem
Suppose that in order for the defendant to be convicted in a jury trial, at least eight of the 12 jurors must enter a guilty vote. Assume each juror makes the correct decision with probability 0.7 independently of other jurors. If 40% of the defendants in such jury trials are innocent, what is the proportion of correct verdicts?
n = 12
need >= 8 to vote guilty to convict
need >= 5 to vote innocent for free
P(indiviudal votes correctly) = .7
P(someone is innocent) = .4
?P(a correct verdict)?
A = innocent
B = jurry reaches correct verdict
?P(B)?
P(B) = P(AnB) + P(AcnB)
= P(A) * P(B|A) + P(Ac) * P(B|Ac)
= .4 * P(B|A) + .6 * P(B|Ac)
P(1 juror votes out of 12)
12 * .7 * .311
CWWWWwWW..W
?P(B|A)?
P(jury reaches correct verdict given they are innocent)
let X = # of correct votes
They have to be innocent so take the probability of all the cases that the jury reaches innocence.
x = 5
n = 12
r = 5 to 12
(12 choose r) * .7r*(.3(12-r))
?P(B|Ac)?
Probabilty that the jurry reaches correct verdict given they are not innocent
3. Exam Info
3.1. Topics
Sample Spaces
General Addition Rule
Permutations and Combinations (formulas provided)
Conditional Probability (formula provided)
Multiplication Rule
Independence
Binomial Probability Distribution
Filling in a PMF Table (PMF stands for Probability Mass Function)
3.2. Exam Rules
50-minute in-class exam
Closed note (i.e. you may not use any notes during the exam)
No calculator
You may raise your hand during the exam if you have questions about clarifications or typos. However, the instructor will not answer questions about concepts or vocabulary.