

Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Material Type: Assignment; Class: PROBABILITY I; Subject: Mathematics; University: University of Texas - Austin; Term: Fall 2007;
Typology: Assignments
1 / 2
This page cannot be seen from the preview
Don't miss anything!


Math 362K Probability Fall 2007 Instructor: Geir Helleloid
Solution. The number of defective diskettes X in a package is a Binomial(10, .01) random variable. The probability that at most 1 of the diskettes in a package is defective is
P (X ≤ 1) = P (X = 0) + P (X = 1)
=
The number of packages Y returned by the customer is itself a Binomial(3, 0. ) random variable, since she returns each of the three packages independently with probability 1-0.9957. So the probability that the customer returns exactly 1 of the 3 packages is
Solution. The number of heads X obtained when flipping coin 1 ten times is a Bino- mial(10, .4) random variable. The number of heads Y obtained when flipping coin 2 ten times is a Binomial(10, .7) random variable. The probability that coin 1 lands heads up exactly 7 times is
The probability that coin 2 lands heads up exactly 7 times is
Let E be the event of getting exactly 7 heads. Then, conditioning on which coin was chosen, we have
P (E) = P (E|coin 1)P (coin 1) + P (E|coin 2)P (coin 2) = P (X = 7) × .5 + P (Y = 7) ×. 5 ≈. 1546
Solution. Let E be the event that the drug is beneficial to the person. Let F be the event that the person gets 2 colds. We want P (E|F ). We know P (E) = .75 and P (Ec) = .25. Furthermore, we can compute P (F |E) and P (F |Ec). Namely, given E, the number of colds that the person gets is a Poisson(3) random variable X, and so
P (F |E) = P (X = 2) = e−^3 ×
Similarly, given Ec, the number of colds that the person gets is a Poisson(5) random variable Y , and so
P (F |Ec) = P (X = 5) = e−^5 ×
Thus, by Bayes’ Formula,
P (F |E)P (E) + P (F |Ec)P (Ec)
≈