Finding Method of Moments Estimates for Uniform Distribution Parameters

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The discussion focuses on finding method of moments estimates for parameters $\alpha$ and $\beta$ of a uniform distribution given the sample data set {2, 3, 5, 9, 10}. The method involves equating theoretical moments to sample moments, specifically using the first moment (mean) and the second moment (variance). The participants emphasize the importance of understanding how to derive these estimates from the provided data and suggest consulting relevant resources for formulas.

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das1
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The problem:

Let the five numbers 2,3,5,9,10 come from the uniform distribution on [$\alpha$,$\beta$]. Find the method of moments estimates for $\alpha$ and $\beta$ .

I am trying to wrap my head around the idea behind estimates of moments. From what I understand, the first moment is the mean, the 2nd moment is variance and the 3rd is the skewness. I want to find the most likely values of both $\alpha$ and $\beta$ , of which the above 5 numbers are between.
The textbook says to equate each theoretical moment with each corresponding sample moment. Not sure how to do this. Can someone help me get started?

Thanks
 
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das said:
The problem:

Let the five numbers 2,3,5,9,10 come from the uniform distribution on [$\alpha$,$\beta$]. Find the method of moments estimates for $\alpha$ and $\beta$ .

I am trying to wrap my head around the idea behind estimates of moments. From what I understand, the first moment is the mean, the 2nd moment is variance and the 3rd is the skewness. I want to find the most likely values of both $\alpha$ and $\beta$ , of which the above 5 numbers are between.
The textbook says to equate each theoretical moment with each corresponding sample moment. Not sure how to do this. Can someone help me get started?

Thanks

Hi das,

Take a look at this section of the relevant wiki page.
It gives the formula for the estimates for $\alpha$ and $\beta$.
Can you apply it? (Wondering)
 
OK thank you I'll try this
 

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