Random Sampling Implementation

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Your question is Random Sampling Implementation. Start with the requirements on the right.

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Problem

How would you implement a function to generate a random sample from a specific distribution? Implement categorical sampling using the inverse transform method. The function receives outcome values, matching probabilities, a sample size, and a random seed, then returns a reproducible list of sampled outcomes. Inputs are values, probabilities, n, and seed; probabilities are nonnegative and sum to 1, and n is nonnegative. Return exactly n values, preserving the supplied outcome types.

Constraints

1 <= len(values) = len(probabilities) <= 10^4
0 <= n <= 1000
0 <= probabilities[i] <= 1
The probabilities sum to 1
All values are valid Python values
The seed is an integer

Function Signature

def sample_distribution(values, probabilities, n, seed):

Your solutionPython 3

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