Sampling Distribution Question

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The discussion focuses on deriving the sampling distribution of a normally distributed random variable, specifically for the statistic Z = (sqrt(N))((x-bar - mu)/(sigma)). It emphasizes the need to derive a test statistic under the null hypothesis H0: mu = mu0, characterizing its distribution and ensuring a type I error probability of alpha. Additionally, it addresses the modifications required when the population variance sigma^2 is unknown. Participants suggest consulting textbooks and existing resources before seeking help, as many foundational concepts are already documented. Understanding these statistical principles is crucial for accurate hypothesis testing and analysis.
hsd
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I've added a screenshot (https://imgur.com/a/isQXZ) and the text below for your convenience.

Please show steps if possible to help my understanding. Thank you.

Consider a random variable that is Normally distributed, with population mean mu = E [X] and population variance sigma^2 = var [X]. Assume that we have a random sample of size N from this distribution. Let x-bar be the usual sample average.

(a) Using the properties of the Normal distribution, derive explicitly the sampling distribution of the random variable: Z = (sqrt(N)) ((x-bar - mu)/(sigma))

(b) Assume that we know sigma^2, but not mu. For the Null hypothesis H0 : mu = mu0, derive a test statistic, characterize its distribution under H0, and describe a test with the property that the probability of committing a type I error is alpha.

(c) How do you need to modify the results in (b) if sigma^2 is unknown.
 
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hsd said:
I've added a screenshot (https://imgur.com/a/isQXZ) and the text below for your convenience.

Please show steps if possible to help my understanding. Thank you.

Consider a random variable that is Normally distributed, with population mean mu = E [X] and population variance sigma^2 = var [X]. Assume that we have a random sample of size N from this distribution. Let x-bar be the usual sample average.

(a) Using the properties of the Normal distribution, derive explicitly the sampling distribution of the random variable: Z = (sqrt(N)) ((x-bar - mu)/(sigma))

(b) Assume that we know sigma^2, but not mu. For the Null hypothesis H0 : mu = mu0, derive a test statistic, characterize its distribution under H0, and describe a test with the property that the probability of committing a type I error is alpha.

(c) How do you need to modify the results in (b) if sigma^2 is unknown.

Are you using a textbook? If so, all you need should be in there.

You are asking us to take the time to write things out and explain them to you, but many other people have already done that and put it into books and on web pages. So: I suggest you start looking elsewhere first, and if you have made a genuine effort---and are still confused about very specific issues---then come back here. General questions like yours will never be well received by most helpers..
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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