Question:

Let 𝑋1, 𝑋2, 𝑋3 be a random sample from an 𝑁(πœƒ, 1) distribution, where πœƒ ∈ ℝ is an unknown parameter. Then, which one of the following conditional expectations does NOT depend on πœƒ ?

Updated On: Nov 17, 2025
  • 𝐸(𝑋1+𝑋2βˆ’π‘‹3 | 𝑋1 + 𝑋2)
  • 𝐸(𝑋1 + 𝑋2 βˆ’ 𝑋3 | 𝑋2 + 𝑋3)
  • 𝐸(𝑋1 + 𝑋2 βˆ’ 𝑋3 | 𝑋1 βˆ’ 𝑋3)
  • 𝐸(𝑋1 + 𝑋2 βˆ’ 𝑋3 | 𝑋1 + 𝑋2 + 𝑋3)
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The Correct Option is D

Solution and Explanation

To determine which conditional expectation does not depend on \(\theta\), we analyze each of the given options. Note that \(X_1, X_2, X_3\) are independent and identically distributed random variables from the normal distribution \(N(\theta, 1)\), having the form:

  1. For a normal distribution \(N(\mu, \sigma^2)\), if \(Y = aX + b\), then \(E(Y) = aE(X) + b\)
  2. The expected value \(E(X_i) = \theta\) for each \(X_i\), since they are distributed as \(N(\theta, 1)\).

Now let's evaluate each option:

  • Option 1: \(E(X_1 + X_2 - X_3 \mid X_1 + X_2)\)
    • The term \(X_1 + X_2\) is sufficient for the conditional expectation. Hence, this depends on \(\theta\).
  • Option 2: \(E(X_1 + X_2 - X_3 \mid X_2 + X_3)\)
    • This can still be influenced by the mean \(\theta\) as it's not independent of other components.
  • Option 3: \(E(X_1 + X_2 - X_3 \mid X_1 - X_3)\)
    • Similar to previous reasoning, \(\theta\) impacts the expectation here.
  • Option 4: \(E(X_1 + X_2 - X_3 \mid X_1 + X_2 + X_3)\)
    • This condition sums all three random variables together. Given that we are summing over all \(X_i\), the overall mean \(\theta\) cancels out, leading to a result that does not depend on \(\theta\).

Hence, the correct answer is the conditional expectation that does not depend on \(\theta\), which is Option 4\(E(X_1 + X_2 - X_3 \mid X_1 + X_2 + X_3)\).

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