3. The joint probability mass function of random variables X and Y is given below:0.20.10.20.25for some real numbers a, BE [0, 1]. We know that the events {X – 0} and {Y - 2} are independent. Determinea and ß. Compute the covariance of X and Y.

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Answered: 3. The joint probability mass function…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

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Problem 1RQ

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Suppose X and Y have the joint probability distribution given by the table shown below. Compute Cov(X,Y). -0.750 O-0.125 -0.625 -0.250 -2 y o 2 0 18 1 BIT 8 x 1 1 4 1 2 0
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Assume the following data displays the joint probability for random variables X and Y: X 10 20 30 20 0.1 0.2 0.05 0.05 0.1 0.2 0.2 0.0 0.1 -1 Y O 1 1. Solve for the correlation of X and Y. 2. Solve for the correlation of X and Y conditional on Y being greater than or equal to zero. 3. Are X and Y independent? Are X and Y conditional on Y being greater than or equal to zero, independent.
Determine whether the statement forms are logically equivalent. In each case, construct a truth table and include a sentence justifying your answer. Your sentence should show that you understand the meaning of logical equivalence. Attachment
A- Let x be a discrete random variable with probability distribution function f(x)=k( x2 +20) and x= −1,1,2,3. Find the value of k. Find the Variance of X. B- Let x denote a discrete random variable which can take the values −2,0, and 5. Given that the expectation of X is 8/100 and P(X=−2)=8/20 , find P(X=5).
Suppose the discrete random variables X and Y are jointly distributed according to the given table. a. Compute the expected values E(X) and E(Y ), the variances V (X) and V (Y ), and also the covariance Cov(X, Y ) of X and Y. b. Determine whether X and Y are independent. c. Let T = X − Y . Compute E(T) and V (T)
he joint pat of the random variable X and Yis iven in the below matrix. Find the mean value f X and Y: P(X,Y)= X 2.45 and 2.1 1.9 and 2.45 O 1.9 and 2.1 2.1 and 2.45 Y 0.05 0.05 0.1 0.05 0.1 0.35 0 0.2 0.1
The possible values of a discrete random variable X are 0, 1, 3, and 6 with respective probabilities 0.2, 0.3, 0.1, 0.4. Find E[X] and Var(X).
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An ordinary (fair) coin is tossed 3 times. Outcomes are thus triples of "heads" (h) and "tails" (t) which we write hth, ttt, etc. For each outcome, let R be the random variable counting the number of heads in each outcome. For example, if the outcome is ttt, then R(ttt) = 0. Suppose that the random variable X is defined in terms of R as follows: X= 2R- 4R-4. The values of X are given in the table below. Outcome ttt tth hht thh tht hhh htthth Value of X -4 -6 -4 -4 -6 -4 Calculate the values of the probability distribution function of X, i.e. the function py. First, fill in the first row with the values of X. Then fill in the appropriate probabilities in the second row. Value x of X Px (x) olo
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3. The joint probability mass function of random variables X and Y is given below: 0.2 0.1 0.2 0.25 for some real numbers a, BE [0, 1]. We know that the events {X – 0} and {Y - 2} are independent. Determine a and ß. Compute the covariance of X and Y.