Finding E(X^2) for a Beta Distribution

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The discussion focuses on finding E(X^2) for a beta distribution with parameters m = n = θ. The user initially struggles to calculate E(X^2) despite knowing that E(X) = 1/2. They reference a formula for variance but realize they can derive E(X^2) using the relationship between variance and expected values. Ultimately, the user resolves their issue by determining E(X) and Var(X), allowing them to calculate E(X^2) correctly. The conversation highlights the importance of understanding the relationships between expected values and variance in statistical calculations.
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Homework Statement



The actual question I'm working on is to find the Method of moments for \theta for a beta distribution where the parameters are m = n= \theta


Homework Equations



What I need help with is to get started, I know that E(X)=1/2 for this question so that it does not depend on \theta My actual problem is that I need to calculate E(X^2) and I can't find any info on how to calculat E(X^2) for a beta distribution, I know the answer is (\theta +1)/(2(2\theta +1))

The Attempt at a Solution



I found a formula on Wiki for Variance of a beta distribution and thought i'd try it, although I know that variance is E(X)^2 - E(X^2) anyway I ended up with 1/(4(2\theta +1)) which was close, but not it... Once I find E(X^2) I should be able to answer the actual question I'm working on

Thanks :)
 
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ahh don't worry I've figured it out, I've got E(X) and I've got Var(X) so I'll find E(X^2) using that formula for variance... thanks anyway
 
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