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- Let {Xn} and {Yn} be sequences of random variables such that Xn diverges to ∞ in probability and Yn is bounded in probability. Show that Xn +Yn diverges to ∞ in probability.Suppose that 2 balls are randomly selected (without replacement) from an urn containing 3 red, 4 blue, and 5 white balls. If we let X and Y denote, respectively, the number of red and white balls chosen. a)Solve for P(x=2) b) Solve for the probability that y is atleast 1 c) Solve for P(x>0)Suppose N = 10 and r = 3. Compute the hypergeometric probabilities for the following values of n and x. n = 4, x = 1. n = 2, x = 2 n = 2, x = 0.
- Suppose the math tutoring lab sees 56 students on a typical Tuesday and that the number of students per day is Poisson distributed. a. Find P(X ≤ 43). What function or formula did you use to answer this question? On my TI-84 Plus, I did a PoissonCDF with Lambda = 56 and the x value = 43. This resulted in 0.04309... Was I correct in using the PoissonCDF, or should I have used the PoissonPDF? b. What is the probability that more than 60 students will come in next Tuesday? Likewise, on my TI-84 Plus, I did a PoissonCDF with Lambda = 60 and the x value = 56. This resulted in 0.7309... Was I correct in assuming that the Lambda is 60 and the x value is 56?Suppose N=10 and r=3 . Compute the hypergeometric probabilities for the following values of and . If the calculations are not possible, please select "not possible" from below drop-downs, and enter 0 in fields. Round your answers, if necessary. a. , (to 2 decimals). b. , (to 3 decimals). c. , (to 4 decimals). d. , (to 2 decimals). e. , (to 2 decimals).For a random walk to be an appropriate model for a time series, which of the following should be true? a. There shouldn't be any significant autocorrelations in the series. b. Except for noise, each value in the series should equal the previous value plus a constant. c. Except for noise, the series should be flat. d. All of these choices are true.
- Suppose X1, X2, ... , Xn is a random sample and Xi = {1, with probability p 0, with probability 1-p} for every i = 1, 2, ... , n. Find the Moment Generating Function of ∑i=1n Xi . What is the distribution of ∑i=1n Xi ?Suppose that we observe that X1, X2, . . . , Xn are iid∼ U(0, 1). Show that X(1)converges in probability to zero.a) Suppose (an) is Cauchy and that for every k ∈ N, the interval (−1/k, 1/k) contains at least one term of (an). Can we say that (an) converges to 0? Either show that it does or give a counter-example.
- An interval within which we expect 95% of all xx's to fall can be defined for any population by applying the ?Use the given sequence to determine the values of n 1 , n 2 , the number of runs G, and the critical values from the table, and use those results to determine whether the sequence appears to be random. Answer parts a-e using alpha equals 0.05. Upper B Upper A Upper B Upper B Upper B Upper B Upper A Upper A Upper B Upper A Upper B Upper A a. Determine the value of n 1 , the number of A's in the sequence: n 1 equalsnothing b. Determine the value of n 2 , the number of B's in the sequence: n 2 equalsnothing c. Determine the number of runs G: Gequals nothing d. Find the critical values from Table A-10. lowerequals nothing upperequals nothing e. State the technical conclusion: A. Do not reject Upper H 0 B. Reject Upper H 0 f. State the final conclusion:The starting time of a class is uniformly distributed between 10:00 and 10:05. If a student arrives early and has to wait t minutes for the class to start, then the student incurs a penalty of At, which accounts for the waste in the student's time. On the other hand, if the student arrives t minutes after the class has started, then the student incurs a penalty of A2t, which accounts for the information the student has missed. If the student arrives at x minutes after 10:00, what is the expected penalty incurred by the student? What value of x minimizes the expected penalty?