We have a random variable, X. Using the variable, we construct a new variable Y, defined
below: Y = 3X+5. Calculate the mean and variance of Y in terms of X.
(i) E(Y)
(ii) Var(Y)
By Theorem:
(1)
(2)
(i)
Here
a = 3
b = 5
Substituting in (1), we get:
(ii)
Substituting in (2), we get
i.e.,
By Theorem:
(1)
(2)
(i)
Here
a = 3
b = 5
Substituting in (1), we get:
(ii)
Substituting in (2), we get
i.e.,
We have a random variable, X. Using the variable, we construct a new variable Y, defined...
3. Suppose we have a random variable X with mean a new random variable Y as = 7 and variance a4. We define Y 3 5X Find the standard deviation of Y
5. Suppose X is a normally distributed random variable with mean μ and variance 2. Consider a new random variable, W=2X + 3. i. What is E(W)? ii. What is Var(W)? 6. Suppose the random variables X and Y are jointly distributed. Define a new random variable, W=2X+3Y. i. What is Var(W)? ii. What is Var(W) if X and Y are independent?
Recall that the variance of a random variable is defined as Var[X]=E[(X−μ)2], where μ = E[X]. Use the properties of expectation to show that we can rewrite the variance of a random variable X as Var [X]=E[X^2]−(E[X])^2 Problem 3. (1 point) Recall that the variance of a random variable is defined as Var X-E(X-μ)21, where μ= E[X]. Use the properties of expectation to show that we can rewrite the variance of a random variable X as u hare i- ElX)L...
2. Explain in words, and words only, the following properties of expected values. NOTE: X and Y are random variables and k is a constant. (a) E(k) = k (b) E(X+Y) = E(X) + E(Y) (c) E(X/Y) + E(X)/E(Y) (d) E(X+Y) E(X)*E(Y) (unless what?) (e) E(X2) # (E(X)]? (1) E(kX) = E(X) 3. For random variable X with mean H. variance is defined var(X) = Ef(X-M.)'. Show how variance can be expressed only in terms of E(X) and E(X). 4....
2. (7 pt) Recall that the variance of a random variable X is defined by Var(X) - E(X - EX)2. Select all statements that are correct for general random variables X,Y. Throughout, a, b are constants. ( Var(X) E(X2) (EX)2 ( ) Var(aX + b) = a2 Var(X) + b2 Var(aXb)a Var(X)+b ( ) Var(X + Y) = Var(X) + Var(Y) ) Var(x) 2 o ) Var(a)0 ( ) var(x") (Var(X))"
Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(x)-5 ECY)4 E(Z)--8 Var (x)-39 Var (Y)-11 Var (z) 37 Compute the values of the expressions below. E(2 -2z) 35 30 Var (sz)-5-D
Suppose that X, Y, and Zare jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(x)-4 E(Y) 2 E(Z)-7 Var (x) -28 Var(Y)-3 Var (Z) -44 Compute the values of the expressions below. E(Y -1) 5Z + 4X Var (4Y-3)
Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(x)-4 E(Y) 2 E(Z)-7 Var (x) -28 Var(Y)-3 Var (Z) -44 Compute the values of the expressions below. E(Y 1) 5Z + 4x Var (4Y-3)
Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(x)-3 E(Y)9 E(Z)-2 Var(X) = 36 par(r)=19 par(Z)-10 Compute the values of the expressions below E (32 +3) 5Y+ 2x Var (5-2)-
Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(X)-8 E(Y)-7 E(Z)-2 Var (x) 24 Var (Y) 2 Var (z) 29 Compute the values of the expressions below. E (5x- 4) Var (-2 5z) - [D