![Use the formulas in the back of the textbook to find the probability density function of X in each of the following cases: (a) X is exponentially distributed and Ex = 13. (b) X has a Gamma distribution with EX = 12 and Var(X) = 36. (c) X has an Inverse Gamma distribution with EX = and Var(X) = 25. (d) X has a Pareto distribution with EX = 5.2 and Var(X) = 63.093333333. Let X be a random variable with an Inverse Gamma distribution with a = 3 and 0 = 4. In each of the following cases, find fy(y), EY, and Var(V). [Hint: Use the formulas at the back of the textbook as needed.] (a) y = x2; (b) y = 9X2 – 17;](http://img.homeworklib.com/questions/dfd30680-ba8d-11eb-b9b8-bfbdb5a78216.png?x-oss-process=image/resize,w_560)
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Use the formulas in the back of the textbook to find the probability density function of...
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise...
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise C fx (x) C0 : where c is a constant. (a) Show that c = 1/7; (b) Graph fx (х); (c) Given that all of the moments exist, why are all the odd moments of X zero? (d) What is the median of the distribution of X? (e) Find E (X2) and hence var X; (f) Let X1, fx (x) What is the limiting...
4. Use the distribution function technique to find the density function for Y = 2X +...
4. Use the distribution function technique to find the density function for Y = 2X + 3 The density function for X is f(x). Your answer should be given as a piecewise function. 2x + 1) 1<x<2 f(x) = 4 0 elsewhere =f2x+1) h 5. Use the transformation technique to find the density function for Y = 4x + 1. The density function for X is f(x). Your answer should be a piecewise function. f(x) = S4e-4x 0 < x...
2-3. Let ?>0 and ?? R. Let X1,X2, distribution with probability density function , Xn be...
2-3. Let ?>0 and ?? R. Let X1,X2, distribution with probability density function , Xn be a random sample from the zero otherwise suppose ? is known. ( Homework #8 ): W-X-5 has an Exponential ( 2. Recall --)-Gamma ( -1,0--) distribution. a) Find a sufficient statistic Y-u(X1, X2, , Xn) for ? b) Suggest a confidence interval for ? with (1-?) 100% confidence level. "Flint": Use ?(X,-8) ? w, c) Suppose n-4, ?-2, and X1-215, X2-2.55, X3-210, X4-2.20. i-1...
Suppose density function positively valued continuous random variable X has the probability a fx(x)kexp 20 fixed...
Suppose density function positively valued continuous random variable X has the probability a fx(x)kexp 20 fixed 0> 0 for 0 o0, some k > 0 and for (a) Find k such that f(x) satisfies the conditions for a probability density function (4 marks) (b) Derive expressions for E[X] and Var[X (c) Express the cumulative distribution function Fx(r) in terms of P(), the stan dard Normal cumulative distribution function (8 marks) (8 marks) (al) Derive the probability density function of Y...
4. Two random variables X and Y have the following joint probability density function (PDF) Skx 0<x<y<1, fxy(x...
4. Two random variables X and Y have the following joint probability density function (PDF) Skx 0<x<y<1, fxy(x, y) = 10 otherwise. (a) [2 points) Determine the constant k. (b) (4 points) Find the marginal PDFs fx(2) and fy(y). Are X and Y independent? (c) [4 points) Find the expected values E[X] and EY). (d) [6 points) Find the variances Var[X] and Var[Y]. (e) [4 points) What is the covariance between X and Y?
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc...
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc useful property of moment generating functions is that they make it relatively casy to compute weighted sums of independent random variables: Z=aX+BY M26) - Mx(at)My (Bt). (A) Derive the MGF for a Poisson random variable X with parameter 1. (B) Let X be a Poisson random variable with parameter 1, as above, and let y be a Poisson random variable with parameter y. X...
11 a) Find the conditional density of T; given that there are 10 arrivals in the...
11
a) Find the conditional density of T; given that there are 10 arrivals in the time interval (0,1). b) Find the conditional density of Ts given that there are 10 arrivals in the time interval (0,1). c) Recognize the answers to a) and b) as named densities, and find the parameters. 11. Suppose X has uniform distribution on (-1,1) and, given X = 1, Y is uniformly distributed on (-V1-22. - 7?). Is (X,Y) then uniformly distributed over the...
1. Consider a continuous random variable X with the probability density function Sx(x) = 3<x<7, zero...
1. Consider a continuous random variable X with the probability density function Sx(x) = 3<x<7, zero elsewhere. a) Find the value of C that makes fx(x) a valid probability density function. b) Find the cumulative distribution function of X, Fx(x). "Hint”: To double-check your answer: should be Fx(3)=0, Fx(7)=1. 1. con (continued) Consider Y=g(x)- 20 100 X 2 + Find the support (the range of possible values) of the probability distribution of Y. d) Use part (b) and the c.d.f....
5. Suppose X has the Rayleigh density otherwise 0, a. Find the probability density function for Y...
5. Suppose X has the Rayleigh density otherwise 0, a. Find the probability density function for Y-X using Theorem 8.1.1. b. Use the result in part (a) to find E() and V(). c. Write an expression to calculate E(Y) from the Rayleigh density using LOTUS. Would this be easier or harder to use than the above approach? of variables in one dimension). Let X be s Y(X), where g is differentiable and strictly incr 1 len the PDF of Y...
Problem(2) (5 points) A continuous distribution has density function k sin(r); 0rST 0; f(x) = otherwise. (a) Find...
Problem(2) (5 points) A continuous distribution has density function k sin(r); 0rST 0; f(x) = otherwise. (a) Find the numerical value of k so that f(r) is a density function. (b) Find E[X] (c) Find E[X2. (d) Find Var X]
Problem(2) (5 points) A continuous distribution has density function k sin(r); 0rST 0; f(x) = otherwise. (a) Find the numerical value of k so that f(r) is a density function. (b) Find E[X] (c) Find E[X2. (d) Find Var X]
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise C fx (x) C0 : where c is a constant. (a) Show that c = 1/7; (b) Graph fx (х); (c) Given that all of the moments exist, why are all the odd moments of X zero? (d) What is the median of the distribution of X? (e) Find E (X2) and hence var X; (f) Let X1, fx (x) What is the limiting...
4. Use the distribution function technique to find the density function for Y = 2X + 3 The density function for X is f(x). Your answer should be given as a piecewise function. 2x + 1) 1<x<2 f(x) = 4 0 elsewhere =f2x+1) h 5. Use the transformation technique to find the density function for Y = 4x + 1. The density function for X is f(x). Your answer should be a piecewise function. f(x) = S4e-4x 0 < x...
2-3. Let ?>0 and ?? R. Let X1,X2, distribution with probability density function , Xn be a random sample from the zero otherwise suppose ? is known. ( Homework #8 ): W-X-5 has an Exponential ( 2. Recall --)-Gamma ( -1,0--) distribution. a) Find a sufficient statistic Y-u(X1, X2, , Xn) for ? b) Suggest a confidence interval for ? with (1-?) 100% confidence level. "Flint": Use ?(X,-8) ? w, c) Suppose n-4, ?-2, and X1-215, X2-2.55, X3-210, X4-2.20. i-1...
Suppose density function positively valued continuous random variable X has the probability a fx(x)kexp 20 fixed 0> 0 for 0 o0, some k > 0 and for (a) Find k such that f(x) satisfies the conditions for a probability density function (4 marks) (b) Derive expressions for E[X] and Var[X (c) Express the cumulative distribution function Fx(r) in terms of P(), the stan dard Normal cumulative distribution function (8 marks) (8 marks) (al) Derive the probability density function of Y...
4. Two random variables X and Y have the following joint probability density function (PDF) Skx 0<x<y<1, fxy(x, y) = 10 otherwise. (a) [2 points) Determine the constant k. (b) (4 points) Find the marginal PDFs fx(2) and fy(y). Are X and Y independent? (c) [4 points) Find the expected values E[X] and EY). (d) [6 points) Find the variances Var[X] and Var[Y]. (e) [4 points) What is the covariance between X and Y?
The moment generating function (MGF) for a random variable X is: Mx (t) = E[e'X]. Onc useful property of moment generating functions is that they make it relatively casy to compute weighted sums of independent random variables: Z=aX+BY M26) - Mx(at)My (Bt). (A) Derive the MGF for a Poisson random variable X with parameter 1. (B) Let X be a Poisson random variable with parameter 1, as above, and let y be a Poisson random variable with parameter y. X...
11
a) Find the conditional density of T; given that there are 10 arrivals in the time interval (0,1). b) Find the conditional density of Ts given that there are 10 arrivals in the time interval (0,1). c) Recognize the answers to a) and b) as named densities, and find the parameters. 11. Suppose X has uniform distribution on (-1,1) and, given X = 1, Y is uniformly distributed on (-V1-22. - 7?). Is (X,Y) then uniformly distributed over the...
1. Consider a continuous random variable X with the probability density function Sx(x) = 3<x<7, zero elsewhere. a) Find the value of C that makes fx(x) a valid probability density function. b) Find the cumulative distribution function of X, Fx(x). "Hint”: To double-check your answer: should be Fx(3)=0, Fx(7)=1. 1. con (continued) Consider Y=g(x)- 20 100 X 2 + Find the support (the range of possible values) of the probability distribution of Y. d) Use part (b) and the c.d.f....
5. Suppose X has the Rayleigh density otherwise 0, a. Find the probability density function for Y-X using Theorem 8.1.1. b. Use the result in part (a) to find E() and V(). c. Write an expression to calculate E(Y) from the Rayleigh density using LOTUS. Would this be easier or harder to use than the above approach? of variables in one dimension). Let X be s Y(X), where g is differentiable and strictly incr 1 len the PDF of Y...
Problem(2) (5 points) A continuous distribution has density function k sin(r); 0rST 0; f(x) = otherwise. (a) Find the numerical value of k so that f(r) is a density function. (b) Find E[X] (c) Find E[X2. (d) Find Var X]
Problem(2) (5 points) A continuous distribution has density function k sin(r); 0rST 0; f(x) = otherwise. (a) Find the numerical value of k so that f(r) is a density function. (b) Find E[X] (c) Find E[X2. (d) Find Var X]
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