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Statistics 8 Online
OpenStudy (hba):

Stats help required

OpenStudy (hba):

OpenStudy (anonymous):

does this have to do with moment generating functions.

OpenStudy (hba):

Moments,Yes.

OpenStudy (anonymous):

hmm, our class is just covering transformations of random variables and distribution method.

OpenStudy (kirbykirby):

What's a moment ratio?

OpenStudy (anonymous):

look it up on google.

OpenStudy (hba):

Um,I don't know.

OpenStudy (kirbykirby):

Is it the same as an L-moment ratio, which keeps popping up on google

OpenStudy (anonymous):

appears so.

OpenStudy (anonymous):

take the first and second moments!

OpenStudy (anonymous):

keep it simple.

OpenStudy (hba):

@electrokid How?

OpenStudy (kirbykirby):

Well the first moment would be your mean, which should be \(2r^2\), but I don' know how you can determine the second moment without knowing the pdf or cdf (or anything else) about he distribution o_O

OpenStudy (anonymous):

hold on, about the notation, \(\mu_k\) is also used to represent the k^th moment!

OpenStudy (kirbykirby):

oh they're using that notation.

OpenStudy (anonymous):

otherwise, use the regular formula \[ {\rm moment}=\int_{-\infty}^\infty(x-\mu)^k(2x^2)dx \]

OpenStudy (anonymous):

this will give you the k^th moment.

OpenStudy (anonymous):

variance is your second moment, k = 2

OpenStudy (hba):

@electrokid I ain't getting anything.

OpenStudy (anonymous):

k=3 -> skewness kurtosis and so on

OpenStudy (hba):

Can we get to the ques?

OpenStudy (anonymous):

tell me, what does \(\mu_r\) represent?

OpenStudy (hba):

r'th moment.

OpenStudy (anonymous):

aha. then no need for the integration 1st moment = mean -> plug in r = 1 2nd moment = variance -> plug in r=2 3rd moment = skewness -> plug in r = 3

OpenStudy (hba):

Okay so i got 1st moment as 2,Second moment as 8 and third moment as 18.

OpenStudy (hba):

Now what?

OpenStudy (hba):

@electrokid

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