Jointly Distributed Random Variables : Uniform Distribution and Joint Probability Density Function
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10. ... Suppose that X and Y are independent with each uniformly distributed on the interval ...
a. What is the joint pdf?
b. What is the probability that they both arrive between ...
c. If the first one to arrive will wait only 10 minutes before leaving to eat elsewhere, what is the probability ...
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Uniform Distribution and Joint Probability Density Function are investigated.
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Solution. (a) By hypothesis, X and Y are independent and follow uniform distribution on [5,6]. So, their pdfs are
and
So, the joint pdf of X and Y is
(b) Since the ...
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."
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