Combining Random Variablesતા=R is a discrete random variable. S is another discrete random variable and is defined by Sis given that E(S)-2 and Var(S) = 9.=Part A Expectation of RFind E(R).Type your formula hereThe following symbols may be useful: E, Ror click here to drag and drop your answerCheck my answerHint 1Useful equationsExpectation of a random variable: E(X) = ΣxP(X = x)Hint 2?Further AC сCP3R+2 It4

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Let Y be a discrete random variable with generating function 4 Gy (s) 6 – s s2 What is Var(Y) (in decimal)? Answer:
J 2 Uncorrelated random variables are not necessarily independent, however. A special situation occurs in the case of jointly Gaussian random variables. For the Gaussian case, uncorrelated random variables are also independent. I donot understand thses sentence. Please explain it through an example.
Let X be the binomial random variable B(10,0.6). Find E(X2). O A. 36 O B. 2.4 С. 38.4 O D. -33.6 E. 8.4
B5. Let X₁, X₂, ..., Xn be IID random variable with common expectation µ and common variance o², and let X = (X₁ + + X₂)/n be the mean of these random variables. We will be considering the random variable S² given by (a) By writing or otherwise, show that S² (b) Hence or otherwise, show that n S² = (x₁ - x)². = Ĺ(X₂ i=1 X₁ X = (X₁-μ) - (x-μ) = Σ(X; -μ)² - n(X - μ)². i=1 ES² = (n-1)0². You may use facts about X from the notes provided you state them clearly. (You may find it helpful to recognise some expectations as definitional formulas for variances, where appropriate.) (c) At the beginning of this module, we defined the sample variance of the values x₁, x2,...,xn to be S = 1 n-1 n i=1 ((x₁ - x)². Explain one reason why we might consider it appropriate to use 1/(n-1) as the factor at the beginning of this expression, rather than simply 1/n. B6. (New) Roughly how many times should I toss a coin for there to be a 95% chance that between 49% and 510/ of my nain toon land Honda?
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(2) Let X be a random variable with p.d.f. ke S(x) ={ *>x>0 , then O.w (a) k-4 (0) k- (d) k-3 (e) None of these (b) k-7 a is the correct answer bis the correct answer c is the correct answer d is the correct answer e is the correct answer
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).
I am really having a difficult time with this problem can you please do it step by step so I can see how you did the calculattions and can you label them as well. Can you please do this step by step and label it .
5
(Revision.) Let X = Wo.5 + 0.5W1 – 2W2 – W3, where (W1, t > 0) is standard BM. Find the expectation E(X²).
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The random variable SN(t)+1 is.. The time until the next event The difference in the current time and the next event The time of the previous event

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R is a discrete random variable. S is another discrete random variable and is defined by S = is given that E(S) = −2 and Var(S) = 9. Part A Expectation of R Find E(R). 3R+2. It 4