![4. Show all your work in this exercise - copying the results from the list with canonical distributions is not sufficient. (a) Consider the Gamma(α, β) distribution (α, β > 0), The MGF for Y ~ Gamma(α, β) is given by my(t) compute EY] and VarlY] (1-St)-α . Use this MGF to (b) The geometric distribution Geom(p) is defined by (1-pf-ıp, p(k) = P(X = k) k=1,2, Show that the MGF for X~Geom(p) is given by pe mx(t)-1-(1 -p)et (c) Use the MGF for X to compute E[X] and Var[X]](http://img.homeworklib.com/questions/04080f40-7032-11ea-a135-a9bf424727ec.png?x-oss-process=image/resize,w_560)
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4. Show all your work in this exercise - copying the results from the list with...
A.6.6. We mentioned in class that the Gamma(, 2) distribution when k is a positive integer is cal...
Please answer A.6.6.:
The previous two questions mentioned above are included
below:
A.6.6. We mentioned in class that the Gamma(, 2) distribution when k is a positive integer is called the Chi-square distribution with k degrees of freedom. From the previous two problems, find the mean, variance, and MGF of the Chi-square distribution with k degrees of freedom. A.6.5. In class we showed that if X ~ Gamma(α, β) then E (X) = aß and uar(X) = αβ2 by using...
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the app...
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the appropriate second derivatives. o? a2 θα β This give a Fisher information matrix /(α, β)::n( ) Inf(a) In r(a) - -a 1(0.19, 5.18) (0.19,5.18) 500 28.983 -0.193 500 NB. ψι(a) d2mT(a)/da2 is known as the trigamma function and is called in R with trigamma. 8/10 00090 Gamma Distribution The inverse matrix 1 0.0422 1.1494 /(α, β)--500 (1.1494 172.5587 Var(a) ~ 8.432 x 10-5 σ& 0.00918 Var(8) 0.3451...
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the appropriate second derivatives....
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the appropriate second derivatives. o? a2 θα β This give a Fisher information matrix /(α, β)::n( ) Inf(a) In r(a) - -a 1(0.19, 5.18) (0.19,5.18) 500 28.983 -0.193 500 NB. ψι(a) d2mT(a)/da2 is known as the trigamma function and is called in R with trigamma. 8/10 00090 Gamma Distribution The inverse matrix 1 0.0422 1.1494 /(α, β)--500 (1.1494 172.5587 Var(a) ~ 8.432 x 10-5 σ& 0.00918 Var(8) 0.3451...
Show all work! Thank you! kxk-1 4.34 Given the pdf for X is f(x)= 10 0<x<1...
Show all work! Thank you!
kxk-1 4.34 Given the pdf for X is f(x)= 10 0<x<1 otherwise determine E[X] and Var[X]. 1 0<x<1 4.35 Given the pdf for X is f(x)=x. determine E[X] and Var[X]. 10 otherwise' Sections 4.5-4.8 A<x<B 4.36 Given a random variable with pdf f(x)= B-A , determine the MGF for this random variable. 10 otherwise so x50 4.37 Given a random variable with pdf f(x)= betx 0<x , determine the MGF for this random variable. '...
Only 1-6) N(4,) "x.xx be a random sample from variance, respectively. In order to show that...
Only 1-6)
N(4,) "x.xx be a random sample from variance, respectively. In order to show that and let X and S be sample mean and sample 1. Let and 5 are independent, tollow the steps below. 1-1) Use the change of variable technique =nx-x,- x and show the joint pdf of ,X,,X is (n-1) n- exp f(,x) 20 2a av2 Use Jacobian for n x n variable transformation 1-2) Use the fact that N(u,a n), and show that the conditional...
1] Assume that the helium porosity (in percentage) of coal sample taken from any particular seam...
1] Assume that the helium porosity (in percentage) of coal sample taken from any particular seam is normally distributed with true standard deviation 0.75. (a) Compute a 90% confidence interval for the true average porosity of a certain seam if the average porosity for 20 specimens from the seam was 4.85. (b) How large a sample size is necessary if the width of the 95% interval for the true average is to be 0.30? 2] A commonly used practice of airline...
2. Consider tossing a coin twice. Denote H ="head" and T ="tail" (a) List all outcomes...
2. Consider tossing a coin twice. Denote H ="head" and T ="tail" (a) List all outcomes in the sample space S (b) Let X count the number of heads. List all outcomes in the events Ao = {X = 0}, Ai = {X=1 and A2 {X = 2}. Are all the events Ao,A1,A2 mutually exclusive? Explain. (c) Suppose P(H) = 0.6. Find the probability mass function of X: f(x) = P{X =x} (d) Find the cumulative distribution function of X:...
Please show full work and explain your work. Thank you. 4·USEFUL THEORETICAL PROBLEMS Tn (26) Assume...
Please show full work and
explain your work. Thank you.
4·USEFUL THEORETICAL PROBLEMS Tn (26) Assume the Binomial distribution, with pmf given by: pn(k) n- ptq 12 where p +q (a) Prove that >Pn(k)1 (b) Find kp(k) (c) Find > kp(k) (d) Find kp(R)kp(k) (27) Assume the Poisson distribution, with pmf given by: p(k)exp (-X).1 (c) Find Σk2p(k) a) Prove that > p(k)- 1 (b) Find Σ kp(k) (d) Find | Σ k-p(k) )-1 Σ kp(k) Use Poisson 10 Use...
Please show all work X, be a random sample from the distribution with the probability density...
Please show all work
X, be a random sample from the distribution with the probability density function Let A0 and let X, X2, f(x; A) 24xe, x>0. a. Find E(X), where k> -8. Enter a formula below. Use* for multiplication, for divison, ^ for power, lam for A, Gamma for the r function, and pi for the mathematical constant . For example, lam k*Gamma(k/2)/pi means Akr(k/2)/T Ax2 or u =x2. Hint 1: Consider u -e"du Hint 2: I'(a) a 0...
1. Let X be an iid sample of size n from a continuous distribution with mean...
1. Let X be an iid sample of size n from a continuous distribution with mean /i, variance a2 and such that Xi e [0, 1] for all i e {1,...,n}. Let X = average. For a E (0,1), we wish to obtain a number q > 0 such that: (1/n) Xi be the sample Р(X € |и — 9. и + q) predict with probability approximately In other words, we wish to sample of size n, the average X...
Please answer A.6.6.:
The previous two questions mentioned above are included
below:
A.6.6. We mentioned in class that the Gamma(, 2) distribution when k is a positive integer is called the Chi-square distribution with k degrees of freedom. From the previous two problems, find the mean, variance, and MGF of the Chi-square distribution with k degrees of freedom. A.6.5. In class we showed that if X ~ Gamma(α, β) then E (X) = aß and uar(X) = αβ2 by using...
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the appropriate second derivatives. o? a2 θα β This give a Fisher information matrix /(α, β)::n( ) Inf(a) In r(a) - -a 1(0.19, 5.18) (0.19,5.18) 500 28.983 -0.193 500 NB. ψι(a) d2mT(a)/da2 is known as the trigamma function and is called in R with trigamma. 8/10 00090 Gamma Distribution The inverse matrix 1 0.0422 1.1494 /(α, β)--500 (1.1494 172.5587 Var(a) ~ 8.432 x 10-5 σ& 0.00918 Var(8) 0.3451...
00900 Gamma Distribution Exercise. To determine the variance of these estimators, compute the appropriate second derivatives. o? a2 θα β This give a Fisher information matrix /(α, β)::n( ) Inf(a) In r(a) - -a 1(0.19, 5.18) (0.19,5.18) 500 28.983 -0.193 500 NB. ψι(a) d2mT(a)/da2 is known as the trigamma function and is called in R with trigamma. 8/10 00090 Gamma Distribution The inverse matrix 1 0.0422 1.1494 /(α, β)--500 (1.1494 172.5587 Var(a) ~ 8.432 x 10-5 σ& 0.00918 Var(8) 0.3451...
Show all work! Thank you!
kxk-1 4.34 Given the pdf for X is f(x)= 10 0<x<1 otherwise determine E[X] and Var[X]. 1 0<x<1 4.35 Given the pdf for X is f(x)=x. determine E[X] and Var[X]. 10 otherwise' Sections 4.5-4.8 A<x<B 4.36 Given a random variable with pdf f(x)= B-A , determine the MGF for this random variable. 10 otherwise so x50 4.37 Given a random variable with pdf f(x)= betx 0<x , determine the MGF for this random variable. '...
Only 1-6)
N(4,) "x.xx be a random sample from variance, respectively. In order to show that and let X and S be sample mean and sample 1. Let and 5 are independent, tollow the steps below. 1-1) Use the change of variable technique =nx-x,- x and show the joint pdf of ,X,,X is (n-1) n- exp f(,x) 20 2a av2 Use Jacobian for n x n variable transformation 1-2) Use the fact that N(u,a n), and show that the conditional...
2. Consider tossing a coin twice. Denote H ="head" and T ="tail" (a) List all outcomes in the sample space S (b) Let X count the number of heads. List all outcomes in the events Ao = {X = 0}, Ai = {X=1 and A2 {X = 2}. Are all the events Ao,A1,A2 mutually exclusive? Explain. (c) Suppose P(H) = 0.6. Find the probability mass function of X: f(x) = P{X =x} (d) Find the cumulative distribution function of X:...
Please show full work and
explain your work. Thank you.
4·USEFUL THEORETICAL PROBLEMS Tn (26) Assume the Binomial distribution, with pmf given by: pn(k) n- ptq 12 where p +q (a) Prove that >Pn(k)1 (b) Find kp(k) (c) Find > kp(k) (d) Find kp(R)kp(k) (27) Assume the Poisson distribution, with pmf given by: p(k)exp (-X).1 (c) Find Σk2p(k) a) Prove that > p(k)- 1 (b) Find Σ kp(k) (d) Find | Σ k-p(k) )-1 Σ kp(k) Use Poisson 10 Use...
Please show all work
X, be a random sample from the distribution with the probability density function Let A0 and let X, X2, f(x; A) 24xe, x>0. a. Find E(X), where k> -8. Enter a formula below. Use* for multiplication, for divison, ^ for power, lam for A, Gamma for the r function, and pi for the mathematical constant . For example, lam k*Gamma(k/2)/pi means Akr(k/2)/T Ax2 or u =x2. Hint 1: Consider u -e"du Hint 2: I'(a) a 0...
1. Let X be an iid sample of size n from a continuous distribution with mean /i, variance a2 and such that Xi e [0, 1] for all i e {1,...,n}. Let X = average. For a E (0,1), we wish to obtain a number q > 0 such that: (1/n) Xi be the sample Р(X € |и — 9. и + q) predict with probability approximately In other words, we wish to sample of size n, the average X...
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