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EastWind [94]
3 years ago
15

Let X and Y again be uniformly distributed independent random variables on [0, 1]. a) Compute the expected value E(XY ). b) What

is the probability density function fZ(z) of Z = XY ? Hint: First compute the cumulative distribution function FZ(z) = P(Z ≤ z) using a double integral, and then differentiate in z. c) Use your answer to b) to compute E(Z). Compare it with your answer to a)

Mathematics
1 answer:
Mariulka [41]3 years ago
7 0

Answer:

a) Computing the expected value E(XY) gives 1/4

b) The probability density function fZ(z) of Z = XY is calculated in the attached picture.

c) Computing E(Z) gives 1/4

Step-by-step explanation:

Comparing the computation of E(Z) using the answer to b), it shows that the values are equal.

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Answer:

The value of the standard error for the point estimate is of 0.0392.

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The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

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For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

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viva [34]

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