Central Limit Theorem Simulation
Probability Theory DS practice problem on Onlearn.
Difficulty: medium.
Topics: Understanding the Central Limit Theorem through Monte Carlo Simulation, Sample Mean, Standard Error, Population Parameters, Shape of Distributions, Asymptotic Normality, Probability Theory, Inferential Statistics, Computational Mathematics, Data Simulation, Stochastic Processes, Sampling Distributions, Law of Large Numbers, Distribution Convergence, Monte Carlo Methods, Random Variable Generation.
Implement a function 'simulate clt(n samples, sample size, distribution type)' that performs a Central Limit Theorem simulation. The function should generate 'n samples' number of means, where each mean is calculated from 'sample size' random variables drawn from the specified 'distribution type' (support 'uniform' [0, 1] and 'exponential' with scale 1.0). Return a list of these calculated means.