Recent content by libragirl79

I understand the breakdown of the x domains, but how do you know where f(x) falls?

right, that's exactly my issue, since i don't have the fcns for 1/4 ≤ x < 1/2 and 1/2 ≤ x < 3/4 ... is there a certain method for doing this?

Homework Statement Given that I have a doubling function : f(x)=2x (for 0≤x<0.5) and 2x-1 (for 0.5≤ x<1) Homework Equations What is f(f(x))? The Attempt at a Solution f(f(x))=4x for the first one and 4x-3 for the second part but not sure what to do about the domain...

Hi, I have been reading SAS docs regarding the code for these two, but I cannot seem to really understand the key difference between them, they almost seem interchangeable to me, although obviously they are not. What is the key difference between the contrast and estimate statement and how...

It's all just theory, I don't have actually any numbers, i goes from 1 to a and j goes from 1 to b. It's yij=mu+alphai+bj+e. I need to somehow use extra sum of squares R(alpha given beta and mu) to get to the quadratic form which would have a non central distribution and divided by the MSE...

Linear Model topic: Given that we have a crossed fixed model w/o interaction, how would I go about testing for the main effects using extra (seq) sum of squares? I know I am supposed to somehow use the F test and get the non centrality parameter but I don't know how to start... Thanks!

Thank you!

Could you please give me a couple of titles? Thanks!

Hi, I am a first year stats grad student and I am taking a class on linear models. The book and lectures focus on the format of definition, proof, lemma, definition, proof, lemma etc. However, I cannot seem to find anywhere some practice problems where I could use these definitions before I...

yeah, I believe if alpha is given, then the MLE for Gamma would be Xbar/alpha. I am just not sure how to get these conditional distributions when doing Rao-Blackwellizing...

No, X1 wouldn't be an unbiased estimator of Beta, since the mean of X1 is alpha*beta given that X1 has gamma dist...

Hi, I have a general concept question. I am working with finding complete sufficient statistics of distributions. Sometimes I need to condition some function of a parameter on a sufficient statistic, using basically Rao-Blackwell, but my trouble is in finding the conditional distributions...

The only way I know how to relate the two was by doing the conditioning I did of both WX on X...It would be optimal if W and X were indep, then the stand result for Cov works perfectly, but that's not the case here...

Thanks for the reply! From what I understand the posed statement is true when E[W|X]=0 a.s. E[W]=E[E[W|X]]=E[0]=0 and the def of cov being E[(W-E(W))(X-E(X))] The question I have is if Expec value of two vars, WX, can be conditioned as I wrote above on X and then X extracted...

Hi, I am trying to show that if the E[W|X]=0 then the Cov (W,X)=0. Using the def of variance, and given that E[W] is zero, I get that Cov is equal to: E[WX]-E[W * E(X)] using conditional expectation: E [E(WX|X)] -E[x]E[W]= E[X E[W|X]]-E[X]E[E(W|X)]=0 I am not sure if...