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Show that the sum of the observations of a random sample of size n from a gamma distribution that has pdf f(x; θ) = (1/θ)e^(−x/θ), 0 < x < ∞, 0 < θ < ∞, zero elsewhere, is a sufficient statistic for θ. Use Neyman's Factorization Theorem.

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Related textbook solutions

Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

The joint probability density function of X and Y is given by

f(x,y)={e-(x+y)   for X>0, y>0      and    0   elsewhere

A. Find the marginal density of X

B. Find the marginal density of Y

C. Find the Conditional density of X given Y

D. Are random variables X and Y independent? State the reason of your answer.

E. Find P(X<.5, y<.5)

F. Find P(X=.5, y<.5)

(1 point) A random sample of 130 observations is selected from a binomial population with unknown probability of success p. The computer value of is 0.64.

    (1) Test : : p = 0.65 against : p > 0.65. Use α= 0.05.

test statistic z =

critical z score

The final conclusion is 

⭕ A. We can reject the null hypothesis that p = 0.65 and accept that p is > 0.65.

⭕ B. There is not sufficient evidence to reject the null hypothesis that p = 0.65.

    (2) Test : p = 0.5 against :p < 0.65. Use α = 0.01.

test statistic z =

critical z score

The final conclusion is 

⭕ A. We can reject the null hypothesis that p = 0.5 and accept that p is < 0.5.

⭕ B. There is not sufficient evidence to reject the null hypothesis that p = 0.5.

   (3) Test : p = 0.55 against : p ≠ 0.55. Use α = 0.01.

test statistic z =

positive critical z score

 

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

  1. (a)  Give the definition of a random variable X on R ∪ {−∞, +∞}.

  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

􏰄3 −1e−λy (y≥0)

[6 marks]

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

    find P(Y < b). Similarly, find P(Y < ∞) and P(Y = −∞). [4 marks]

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

    your answer. [1 marks]

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