Consider the sample space S = [0, 1] with a probability measure that is uniform on this space, i.e. P([a, b) = b – a, for all 0 < a < b < 1. Define the sequence {X,,n = 1, 2, · .} as follows: ... n+1 2n 1 X,(s) = otherwise Also, define the random variable X on this sample space as follows: 1 0
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- 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?1.) The amount of time an air-conditioning technician to repair a unit is in between 1.9 and 5 hours which is found to be uniformly distributed. Let x be the time needed to fix an A/C unit. a.) Find the probability that a randomly selected A/C unit repair requires more than 2.5 hours?Generate a sequence U1, U2,..., U1000 of independent uniform random variables on a computer. Let Sn = ni=1 Ui for n = 1, 2,..., 1000. Plot each ofthe following versus n:a. Snb. Sn/nc. Sn − n/2d. (Sn − n/2)/ne. (Sn − n/2)/√nExplain the shapes of the resulting graphs using the concepts of this chapter.
- 1.) The amount of time an air-conditioning technician to repair a unit is in between 1.9 and 5 hours which is found to be uniformly distributed. Let x be the time needed to fix an A/C unit. b.) Find the probability that a randomly selected A/C unit repair requires less than 3.5 hours?16 - Calculate the 1-ci and 2-ch moments according to the arifmetic mean of the following simple sales series (pieces). A) m1 = 0 m2 = 16,67 B) m1 = 0,6 m2 = 11,67 C) m1 = 0.4 m2 = 10.67 D) m1 = 0 m2 = 11,67 E) m1 = 2 m2 = 11,67Give any example of a probability distributionover x and y for a classification problem on the real line, so that the Bayesoptimal classifier isf(x) =1, if x ∈[1, 3] ∪[6, 7]−1, otherwise
- Consider a dicrete uniform random variable X over the set {1, 2, ..., k} where k = 12 The event A is defined as A = {k - 2, k - 1, k}. Find P[X=k|A]Which assumption do you need for the central limit theorem? Select one: a. The sequence X1, X2,… has to be independent, identically distributed with finite mean and non-zero variance. b. The sequence X1, X2,… has to be independent with finite mean and variance. c. The sequence X1, X2,… has to be independent, identically distributed with finite mean and variance. d. The sequence X1, X2,… has to be Bernoulli distributed, independent and with finite mean and non-zero variance.Q14 Buses arrive at a specified stop at 15-minute intervals starting at 7 A.M. That is, they arrive at 7:00, 7:15, 7:30, 7:45, and so on. If a passenger arrives at the stop at a time that is uniformly distributed between 7:00 and 7:30, what is the probability that she waits more than 10 minutes for a bus?
- Suppose X is a discrete random variable which only takes on positive integer values. For the cumulative distribution function associated to X the following values are known: F(13)=0.36F(21)=0.41F(26)=0.44F(33)=0.5F(40)=0.55F(48)=kF(54)=0.63F(60)=0.69 Assuming that Pr[21<X≤48]=0.18, determine the value of k.b) Use the linear congruential method to generate a sequence of 5 random numbers with given seed of 27, increment 43 and constant multiplier 17, modulus 100c) i. If an M/M/1 queue has utilization of 90%, what do you think will be the average queue length and the average response time? If the arrival rate is 100 jobs per secondii. If an M/D/1 queue has utilization of 80% do you expect its mean queue length and response time to be less, same, or greater than that of an M/M/1? Explain your answer.The Central Limit Theorem says A. When n>30n>30, the sampling distribution of x¯¯¯x¯ will be approximately a normal distribution.B. When n<30n<30, the original population will be approximately a normal distribution.C. When n>30n>30, the original population will be approximately a normal distribution.D. When n<30n<30, the sampling distribution of x¯¯¯x¯ will be approximately a normal distribution.E. None of the above