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The random variables Theta and

Let X_1,X_2,\dots ,X_ n be random variables; which are i.i.d., conditional on \theta, and such that,p(X_ i|\theta )=N(\theta
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Suppose that X_1=\Theta +W_1 and X_2=2\Theta +W_2, where \Theta ,W_1,W_2 are independent standard normal random variables. If
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Suppose that X_1=\Theta +W_1 and X_2=2\Theta +W_2, where \Theta ,W_1,W_2 are independent standard normal random variables. If
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Recall from the setup that X_1,\ldots ,X_ n\sim X are i.i.d. random variables with density f_\theta, for some unknown \theta \in
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Recall from the setup that X_1,\ldots ,X_ n\sim X are i.i.d. random variables with density f_\theta, for some unknown \theta \in
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Let Θ1, Θ2, W1, and W2 be independent standard normal random variables. We obtain two observations,X1=Θ1+W1,X2=Θ1+Θ2+W2.
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2. asked by panda
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Let Θ1, Θ2, W1, and W2 be independent standard normal random variables. We obtain two observations,X1=Θ1+W1,X2=Θ1+Θ2+W2.
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2. asked by Anonymous
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As in the last video, let X=\Theta +W, where \Theta and W are independent normal random variables and W has mean zero.a) Assume
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X_1,\ldots ,X_ n\sim X are i.i.d. random variables with density f_\theta, for some unknown \theta \in (0,1):f_\theta (x)=\left\{
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The random variables Theta and X are described by a joint PDF which is uniform on the triangular set defined by the constraints
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2. asked by Ramya
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