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Suppose that Y is a random variable with the probability mass function, 2 k PſY = k] = nom 1, for k=0, 1, ..., n - 1, n (n − 1)? where n > 2. 1. Derive the expected value of Y. 2. Evaluate the second moment of Y. 3. Determine the variance of Y.

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Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

Q5. Let (Ω, F , P) be a probability space. Let λ > 0 be some constant.

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  2. (b)  Define the distribution function FX for the RV X.

[6 marks]

[1 marks]

[1 marks] (c) Suppose that Y is a RV on R ∪ {−∞, +∞} with distribution function given by

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page1image62001664 page1image62003968

FY (y) = 4 2 1

(y < 0).
For any a < b, determine P(Y > a), and P(Y ∈ (a, b]). [3 marks]

  1. (d)  By noting {Y < b} = ∪n∈N{Y ≤ b − 1 } and using Continuity of Probability, n

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  2. (e)  Is Y either a discrete RV, or a continuous RV, or a mixture of both? Explain

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3. Consider any Random Walk W = (Wn)n≥0 on Z, that is, Wn := a + X1 + · · · + Xn whereX1,X2,... areIIDRVs.
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（see the picture）

You are given a fair die, i.e. the outcomes of any throw are contained in the sample space   Let the event A be that an even number is thrown and the event B that a multiple of three is thrown. Now consider the two random variables X and Y. X takes on a value of 1 if the event A has occurred and the value 0 if A has not occurred. The random variable Y takes on the value of 1 if the event B has occurred and the value zero if B has not occurred.

(a) Derive the joint pdf of X and Y. Provide this in the form of a table

                                        Y=0                                Y=1

X=0    
X=1    

b) What is the marginal probability distribution of Y?
(c) What is the conditional probability distribution of X, given that Y = 1?
(d) What is E (X|Y = 1)?
(e) What is Cov (X, Y )?
(f) Are X and Y independent random variables?

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