Just the last part please :) Consider the following distributions for a random variable X. In...
i) CHOOSE which of these probability distributions is most appropriate to describe a random variable X defined as "the number of approved state-government construction contracts bid by the engineering firm in the recent year". * X~Poisson(8) X~Po(3.2) X~Binomial(8,0.4) X~Negative Binomial(8,0.4) X~Geometric(0.4)ii) Using the random variable X in question 1(i), which of the following mathematical expressions indicates: the probability that the engineering firm will not get any state-government construction contracts that they have bid in the recent year? * P(X=8) P(X...
O RANDOM VARIABLES AND DISTRIBUTIONS Expectation and variance of a random variable Let X be a random variable with the following probability distribution: Value x of X P(X-) 0.35 0.40 0.10 0.15 10 0 10 20 Find the expectation E (X) and variance Var(X) of X. (If necessary, consult a list of formulas.) Var(x) -
Please answer from a-d
Problem 2. Let X be a random variable with one of the following cumulative distribution function. 1.2 1,2 1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 -1.0 -0.5 0.0 0.5 1.0 1.5 2,0 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 X X Pick the correct cumulative distribution function plot and answer questions: Page 2 of 9 Write down the probability mass function and What is the PMF of X? A. Poisson (3...
(4) For each of the following distributions, write the support for the random variable and calculate the second absolute moment. a. X ~ normal (0,1) b. Y ~ binomial (100,0.2) c. Z ~ Poisson (1)
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2. Discrete and Continuous Probability Distributions: In the following three parts, write the formula and value for the cases shown. (a) X is the binomial random variable with n = 50 and p = 0.65. [8 points) Case Excel Formula Value PIX> 25) P(X < 35) OMBE 2787 Makeup Test Summer 2020 (b) Suppose that a bank receives an average of 7 bad checks per day and this process can be modeled as a Poisson distribution....
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10. If X is a binomial random variable with parameters n, 2, and Y is a Poisson rand om variable with parameter λ =np, then for 0 < k < n, (A) P(X = k) P(Y k) for large n (B) P(X = k) P(Y (C) P(X k) P(Y k) for small p = k) for large n and small p
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1.2 Sum of the Independent Random Variables Consider a set of 'n random variables XI,Xy . . . Х,, . Let's define the random variable Y as the stinmation of all X, variables: A) For the case m 10 and Xis being independent uniform variables in the interval -0.5,0.5, generate 100,000 samples of Y. Use the discretization technique from the previous section for the [-5,5 interval and plot the pmf of Y B) Now increase m to...
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Problem 2. Let X be a random variable with one of the following cumulative distribution function. 1.2 1.2 1.0 1.0 0.8 0.8 0.6 0.6 0.4 F 0.4 0.2 0.2 0.0 0.0 -1.0 -0.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 0.0 0.5 1.0 1.5 2.0 X Pick the correct cumulative distribution function plot and answer questions: Page 2 of 9 (3 pts) Write down the probability mass function and What is the PMF of...
a) Consider the following data on a variable that has Bernoulli distribution: X P (X) 0 0.3 1 0.7 Find the Expected value and the variance of X. And E(X)-X Px) b) Consider the following information for a binomial distribution: N number of trials or experiments 5 x- number of success 3 Probability of success p 0.4 and probability of failure 1-p 0.6 Find the probability of 3 successes out of 5 trials: Note P(x) Nox p* (1-p)Note: NcN!x! (N-x)!...
Problem 5: 10 points Assume that a discrete random variable, N, is Poisson distributed with the rate, λ = 3. Given N = n, the random variable, X, conditionally has the binomial distribution, Bin [N +1, 0.4] 1. Evaluate the marginal expectation of X. 2. Evaluate the marginal variance of X