To Whom This May Concern, Can you help me with a problem from the James Evans \'

Question

To Whom This May Concern,

Can you help me with a problem from the James Evans 'Business Analytics' textbook (edition 2 or later)? Specifically, in chapter 6 there is a case studay at the end of the chapter. Question 5 (of 6) was not answered yet. This website refers to it as 5CP. I've placed a link to the question below, but it reads "For the data in the worksheet Blade Weight, what is the sampling distribution of the mean, the overall mean and the standard error of the mean? Is a normal distribution an appropriate assumption for the sampling distribution of the mean?"

I'm hoping for a complete step-by-step answer. I'm stuck on how to even start because I'm not sure how to get the 'sampling distribution of the means'. Does that mean I need to take a random sample of the data set in Excel? I don't think that is the case. And if I take the average of all 350 weights I don't know how that would differ from the 'overall mean'.

http://www.chegg.com/homework-help/Business-Analytics-2nd-edition-chapter-6-problem-5CP-solution-9780321997821

Thank you in advance for all of your help!

Explanation / Answer

You have total of 350 weights . The distribution of these weights is not known. Now, if you take repeated samples from this, say of a size=20, and take 50 such samples, and then plot the means of all samples( we get 50 means, a value corresponding to each sample of size 20). This plot of means is called Sampling Distribution of Mean.

If you simply take the average of all 350 values, it is Overall Mean.

The Sampling Distribution of mean that we got above, if we take its standard deviation , we get Standard Error of Mean.

Yes, Normal Distribution is an appropriate assumption for the Sampling Distribution of Mean , as stated by Central Limit Theorem. The 350 weights may not follow Normal Distribution but if we take repeated samples from it and plot their means , it will follow normal distribution irrespective of the distribution of 350 weights.

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