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D.) Suppose X1 and X2 are independent exp. random variables, each with mean data and y=X1 and X2. What is the moment generating function for the random variable y?

Which choice below is right:

1.) My = (1-t/beta)^-2

2.) My = (1-t/beta)^2

3.) My = (1-beta*t)^-2

4.) My = (1-beta*t)^2

E.) Let X1 and X2 be two different random variables with Poissan's dist. with parameters mew(subscript1)=2 and mew(subscript 2)=3, respectively. Let random variable Y1=X1 +X2. The probability that X1 = 5 is:

1.) 0.0006

2.) 0.1755

3.) 0.0141

4.) 0.1606

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Solution Summary

The moment generating functions and Poissan's distribution are determined. The random variables are determined.

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Statistics, All Topics
Year 1
Moment generating function and Poissan's Dist.
________________________________________
Two different problems with multiple choice answers

D.) Suppose X1 and X2 are independent exp. random variables, each with mean beta and y=X1 and X2. What is the moment generating function for the random variable ...

Solution provided by:
Changping Wang, MA
Education
  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "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"
  • "Thank you very much for your valuable time and assistance!"
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