A random sequence Xn is defined by X, = A(n-K) u[n – K] where A and K are statistically independent random variables, and u[·] is a unit step sequence. Random variable A is uniformly distributed between 0 and 1. Random variable K is a discrete random variable which takes values equal to -1,0, and 1 with equal probability. (a) Determine the mean sequence µx[n] and plot its values for n = -1,0,1,2,3. (b) Determine the auto-correlation bi-sequence Rx[m,n]. (c) Comment on the stationarity of Xņ.
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- A simple random sample X1, …, Xn is drawn from a population, and the quantities ln X1, …, ln Xn are plotted on a normal probability plot. The points approximately follow a straight line. True or false: a) X1, …, Xn come from a population that is approximately lognormal. b) X1, …, Xn come from a population that is approximately normal. c) ln X1, …, ln Xn come from a population that is approximately lognormal. d) ln X1, …, ln Xn come from a population that is approximately normal.2) The time between successive customers coming to the market is assumed to have Exponential distribution with parameter l. a) If X1, X2, . . . , Xn are the times, in minutes, between successive customers selected randomly, estimate the parameter of the distribution. b) b) The randomly selected 12 times between successive customers are found as 1.8, 1.2, 0.8, 1.4, 1.2, 0.9, 0.6, 1.2, 1.2, 0.8, 1.5, and 0.6 mins. Estimate the mean time between successive customers, and write down the distribution function. c) In order to estimate the distribution parameter with 0.3 error and 4% risk, find the minimum sample size.The random variable X has a Bernoulli distribution with parameter p. A random sampleX1, X2, . . . , Xn of size n is taken of X. Show that the sample proportionX1 + X2 + · · · + Xnnis a minimum variance unbiased estimator of p.Given that X1, X2, . . . , Xn forms a random sample of size n from a geometric population withparameter p, show thatY =n∑j=1
- In bacterial counts with a haemacytometer, the number of bacteria per quadrat has a Poisson distribution with probability mass function f(x), where f(x) = θ x e −θ/x! and θ is to be estimated. If there are many bacteria in a quadrat, it is difficult to count them all, and so the only information recorded is that the number of bacteria exceeds a certain limit c, a large positive integer. In a random sample of n quadrats, it was.b and c part Buses arrive at the station according to a Poisson process at a rate of lambda = 0.4 per minute. Assume at the starting condition is time = 0. Imagine when a bus stops, the probability 1 person gets off at the bus station is p = 0.7, and the probability 2 people get off is p = 0.3, independent of everything else. Let X denote the number of people that get off at the bus station in the first 5 minutes. a) Find E[X] b) Calculate P{X = 2} c) Compute Var(X)Which of the following statements are true (no need to justify)?(1) The transformation of a continuous random variable is always a continuous random variable.(2) The distribution of the transformation of a random variable is always the same as that of the original sat-distribution of the univariate.(3) Many random variables can be represented by a uniformly distributed random variableusing if the quantile function of the distribution is known.(4) The accumulation function of several variables is increasing with respect to each variablefunction.(5) The multidimensional accumulation function is determined by its (one-dimensional) marginal distributionwhere from.(6) The marginal distributions of a discrete random vector are discrete distributions.