What is the distribution of the random vector
[
𝑋
2

𝑋
3
]
?

Question

What is the distribution of  the random vector
[
𝑋
2

𝑋
3
]
?

BlackTom AI · Accepted Answer

Let's parse the question carefully and lay out what each option is asserting about the distribution of the random vector [X^2, X^3].
Option 1: 'We cannot determine the distribution, but we can state that μ = [2, 3] and Σ = [[1, 0], [0, 4]].' This statement attempts to specify both a distribution form and parameter values, but it claims we cannot determine the distribution while also giving a precise claim about μ and Σ. In typical multivariate normal context, if the question asks for the distribution under a standard assumption (e.g., the vector being jointly normal with a given mean vector and covariance), we can determine the distribution form and its parameters. The pairing of 'cannot determine' with explicit μ and Σ is inconsistent unless more context is provided, so as a stand-alone claim, this option is dubious and misleading.
Option 2: 'There is not enough information provided to answer this question.' This would be true if we lacked any specification about the joint distribution, mean, or covariance. However, the prompt (and the given answer field in the data) explicitly supplies a mean vector μ = [2, 3] and a covariance structure Σ = [[1, 0], [0, 4]]. With that information, under the common assumption that the vector is jointly normal, we do indeed have a well-defined bivariate normal distribution. Therefore, saying there is not enough information ignores the data already given, making this option incorrect.
Option 3: 'It follows a bivariate normal distribution with μ = [2, 3], but Σ is unknown.' This option correctly identifies the mean but leaves the covariance matrix unspecified. Since the question data includes a proposed Σ = [[1, 0], [0, 4]], claiming Σ is unknown is inconsistent with the provided information and the standard interpretation that the given Σ is part of what defines the distribution. Hence this is not the right characterization given the stated context.
Option 4: 'It follows a bivariate normal distribution with μ = [2, 3] and Σ = [[1, 0], [0, 4]].' This option directly matches the provided mean vector and covariance matrix. It asserts both the distribution family (bivariate normal) and the exact parameters, aligning with the typical specification that a pair of jointly normal components is described by a mean vector and a 2x2 covariance matrix. The structure Σ = [[1, 0], [0, 4]] expresses independence between the two components (zero covariance) and unit variance for the first component with a larger variance for the second, which is consistent with a clear, positive-definite covariance.
In summary,Option 1 conflates incompatibility between a stated distribution form and an implicit claim of insufficient information.Option 2 ignores the given μ and Σ entirely.Option 3 partially acknowledges μ but negates Σ contrary to the data.Option 4 coherently combines the specified μ and Σ into a standard bivariate normal description, matching the supplied information and typical interpretation for such a problem.

25S-STATS-102B-LEC-3 Quiz 5- Requires Respondus LockDown Browser

What is the distribution of the random vector [ 𝑋 2 𝑋 3 ] ?

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