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01. 125 marks Find the approximate distribution of y.. (sample median) when the population has; a)...
1. Select all true statements about sample mean and sample median. A) When the population distribution...
1. Select all true statements about sample mean and sample median. A) When the population distribution is skewed, sample mean is biased but sample median is an unbiased estimator of population mean. B) When the population distribution is symmetric, both mean and sample median are unbiased estimators of population mean. C) Sampling distribution of sample mean has a smaller standard error than sample median when population distribution is normal. D) Both mean and median are unbiased estimators of population mean...
3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume...
3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume the prior distribution of Of λ is is an exponential with mean 1, i.e. the prior pdi g(A) e-λ, λ > 0 Note that the exponential distribution is a special gamma distribution; and a general gamma distribution with parameters α > 0 and β > 0 has the pd.f. h(A; α, β)-16(. otherwise Also the mean of a gamma random variable with the pd.f.h(Χα,...
3. (20 marks) Suppose Y...Y is a random sample of independent and identically distributed Gamma(c...
3. (20 marks) Suppose Y...Y is a random sample of independent and identically distributed Gamma(c, B) random variables. Suppose c is a known constant. a) (5 marks) Find an exact (I-a)100% CI. forty: cß based on Y. Hint: Make use of the Chi-Square distribution when finding your pivot. b) (5 marks) Find an approximate (1-α)100% CI. forMy-cß based on only Y using a n (Y-CB) ~ Normal (0, Normal approximation and the pivot Z- c) (5 marks) Find an approximate...
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a) Suppose that α 4 is known and β is unknown. Find a complete sufficient statistic for β. Find the MVUE of β....
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a) Suppose that α 4 is known and β is unknown. Find a complete sufficient statistic for β. Find the MVUE of β. (Hint: What is E(Y)?) (b) Suppose that β 4 is known and α is unknown. Find a complete sufficient statistic for a.
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a)...
2- 5. The Weibull distribution has many applications in reliability engineering, survival analysi...
2- 5. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let B>0, 8>0. Consider the probability density function x>0 zero otherwise Recall (Homework #1) V-Χδ has an Exponential(8-T )-Gamma(u-l,e-1 ) distribution. Let X1, . , X/ be a random sample from the above probability distribution. y-ΣΧ.Σν i has a Gamma(u-n, θ- 1 ) distribution. !!! i-l 2. suppose δ is known. Let Xi, X2, , Xn be a random sample from the distribution with...
9. (5 marks) Consider a Gamma random variable, Y ~ Ganzma(α = n/2, β). Find the...
9. (5 marks) Consider a Gamma random variable, Y ~ Ganzma(α = n/2, β). Find the moment- generating function of U = c Y. If U ~ , what is c?
Suppose X and Y are independent and Prove the following a) U=X+Y~gamma(α + β,γ) b) V=X/(X...
Suppose X and Y are independent and
Prove the following
a) U=X+Y~gamma(α + β,γ)
b) V=X/(X + Y ) ∼ beta(α,β)
c) U, V independent
d) ~gamma(1/2,
1/2) when W~N(0,1)
X ~ gammala, y) and Y ~ gamma(6, 7) We were unable to transcribe this image
1. Suppose that Y ∼ Gamma(α, β) and c > 0 is a constant. (a) Derive the density function of U ...
1. Suppose that Y ∼ Gamma(α, β) and c > 0 is a constant. (a)
Derive the density function of U = cY. (b) Identify the
distribution of U as a standard distribution. Be sure to identify
any parameter values. (c) Can you find the distribution of U using
MGF method also?
I. Suppose that Y ~ Gamma(α, β) and c > 0 is a constant. (a) Derive the density function of U cY. (b) Identify the distribution of U...
Problem 1. (5 marks. 3. 2) Assume X ~ Gamma(01, β) and Y ~ Gamma(O2, β)...
Problem 1. (5 marks. 3. 2) Assume X ~ Gamma(01, β) and Y ~ Gamma(O2, β) are independent random variables. a) Compute the Joint density of U = X + Y and V X X + Y , be sure to include the support/domain. b) Based on the joint density derived in part (a) find the marginal densities of U and V, be sure to include the support (s)/domain(s). Explicitly state the name of the distributions of U and V...
A) Find the variance of each unbiased estimator. b) Use the Central Limit Theorem to create an ap...
a) Find the variance of each unbiased estimator.
b) Use the Central Limit Theorem to create an approximate 95%
confidence interval for theta.
c) Use the pivotal quantity Beta(alpha=13, beta=13) to create an
approximate 95% confidence interval for theta.
d) Use the pivotal quantity Beta(alpha=25, beta=1) to create an
approximate 95% confidence interval for theta.
Suppose that Xi, , x25 are i.i.d. Unifom(0,0), where θ is unknown. Consider three unbiased estimators of 6 25 26 25 25 26 max (X...,...
3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume the prior distribution of Of λ is is an exponential with mean 1, i.e. the prior pdi g(A) e-λ, λ > 0 Note that the exponential distribution is a special gamma distribution; and a general gamma distribution with parameters α > 0 and β > 0 has the pd.f. h(A; α, β)-16(. otherwise Also the mean of a gamma random variable with the pd.f.h(Χα,...
3. (20 marks) Suppose Y...Y is a random sample of independent and identically distributed Gamma(c, B) random variables. Suppose c is a known constant. a) (5 marks) Find an exact (I-a)100% CI. forty: cß based on Y. Hint: Make use of the Chi-Square distribution when finding your pivot. b) (5 marks) Find an approximate (1-α)100% CI. forMy-cß based on only Y using a n (Y-CB) ~ Normal (0, Normal approximation and the pivot Z- c) (5 marks) Find an approximate...
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a) Suppose that α 4 is known and β is unknown. Find a complete sufficient statistic for β. Find the MVUE of β. (Hint: What is E(Y)?) (b) Suppose that β 4 is known and α is unknown. Find a complete sufficient statistic for a.
with parameters α and β. 2. Yİ,%, , Y, are a random sample from the Gamma distribution (a)...
2- 5. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let B>0, 8>0. Consider the probability density function x>0 zero otherwise Recall (Homework #1) V-Χδ has an Exponential(8-T )-Gamma(u-l,e-1 ) distribution. Let X1, . , X/ be a random sample from the above probability distribution. y-ΣΧ.Σν i has a Gamma(u-n, θ- 1 ) distribution. !!! i-l 2. suppose δ is known. Let Xi, X2, , Xn be a random sample from the distribution with...
9. (5 marks) Consider a Gamma random variable, Y ~ Ganzma(α = n/2, β). Find the moment- generating function of U = c Y. If U ~ , what is c?
Suppose X and Y are independent and
Prove the following
a) U=X+Y~gamma(α + β,γ)
b) V=X/(X + Y ) ∼ beta(α,β)
c) U, V independent
d) ~gamma(1/2,
1/2) when W~N(0,1)
X ~ gammala, y) and Y ~ gamma(6, 7) We were unable to transcribe this image
1. Suppose that Y ∼ Gamma(α, β) and c > 0 is a constant. (a)
Derive the density function of U = cY. (b) Identify the
distribution of U as a standard distribution. Be sure to identify
any parameter values. (c) Can you find the distribution of U using
MGF method also?
I. Suppose that Y ~ Gamma(α, β) and c > 0 is a constant. (a) Derive the density function of U cY. (b) Identify the distribution of U...
Problem 1. (5 marks. 3. 2) Assume X ~ Gamma(01, β) and Y ~ Gamma(O2, β) are independent random variables. a) Compute the Joint density of U = X + Y and V X X + Y , be sure to include the support/domain. b) Based on the joint density derived in part (a) find the marginal densities of U and V, be sure to include the support (s)/domain(s). Explicitly state the name of the distributions of U and V...
a) Find the variance of each unbiased estimator.
b) Use the Central Limit Theorem to create an approximate 95%
confidence interval for theta.
c) Use the pivotal quantity Beta(alpha=13, beta=13) to create an
approximate 95% confidence interval for theta.
d) Use the pivotal quantity Beta(alpha=25, beta=1) to create an
approximate 95% confidence interval for theta.
Suppose that Xi, , x25 are i.i.d. Unifom(0,0), where θ is unknown. Consider three unbiased estimators of 6 25 26 25 25 26 max (X...,...
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