# Jointly Distributed Random Variables : Gamma and Exponential Distributions

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If X1, X2,...Xn are all independent Expo(λ), and Sn=Σ i=1..n Xi, then Sn≈Gamma (n,λ). Show that this is true when n=2.

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Gamma and Exponential Distributions with regard to Jointly Distributed Random Variables are investigated. The solution is detailed and well presented. The response received a rating of "5" from the student who originally posted the question.

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(This problem is from the chapter of Jointly Distributed Random Variables.)

Before I prove this question, I would like to recall the Exponential random variable and Gamma distribution.

A random variable is said to have a gamma distribution with parameters if its density function is

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###### Education

- BSc , Wuhan Univ. China
- MA, Shandong Univ.

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- "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
- "excellent work"
- "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
- "Thank you"
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