Use the law of iterated expectation to calculate
Suppose we have a stick of length L. We break it once at some point X _ Unif(0;L). Then we break it again at some point Y _ Unif(0;X). Use the law of iterated expectation to calculate E[Y ].
Expert
X is the length of the stick after we break for the ?rst time. Y is the length after the second time.
We have E[ Y | X ] = X /2, since the breakpoint is chosen uniformly over the length X of the remaining stick. similarly, E[X ] = L/2.
E[Y] = E[E [Y | X ] ]= E[X/2]=E[X]/2 = L/4
Random variables with zero correlation are not necessarily independent. Give a simple example.
It doesn't rain often in Tucson. Yet, when it does, I want to be prepared. I have 2 umbrellas at home and 1 umbrella in my office. Before I leave my house, I check if it is raining. If it is, I take one of the umbrellas with me to work, where I would leave it. When I
What are the Bayesian Point of estimation and what are the process of inference in Bayesian statistics?
File is attached, need it by 8:30 AM Pacific (Seattle, WA) time. No delay acceptable. Need it March 25, 2014 on 8:30 AM Pacific time.
Distinguish between discrete and continuous data in brief.
A nurse practitioner working in a dermatology clinic is studying the efficacy of tretinoin in treating women’s post partum abdominal stretch marks. From a sample of 15 women, the mean reduction of stretch mark score is -0.33 with a sample standard deviation of 2.46. Describe what happens to the c
Suppose that your utility, U, is a function only of wealth, Y, and that U(Y) is as drawn below. In this graph, note that U(Y) increases linearly between points a and b. Suppose further that you do not know whether or not you
what are the advantages and disadvantages of seasonal variation
1. A popular resort hotel has 300 rooms and is usually fully booked. About 4% of the time a reservation is canceled before 6:00 p.m. deadline with no penalty. What is the probability that at least 280 rooms will be occupied? Use binomial distribution to find the exact value and the normal approxi
Discuss the following statements and explain why they are true or false: a) Increasing the number of predictor variables will never decrease the R2 b) Multicollinearity affects the int
18,76,764
1948039 Asked
3,689
Active Tutors
1445337
Questions Answered
Start Excelling in your courses, Ask an Expert and get answers for your homework and assignments!!