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Learn the Central Limit Theorem in statistics with definition, formula, proof, and examples. Understand its importance, solved problems, and applications for JEE and advanced level exams. The Central Limit Theorem (CLT ) relies on multiple independent samples that are randomly selected to predict the activity of a population. The Central Limit Theorem (CLT) proves that the averages of samples from any distribution themselves must be normally distributed. Consider IID random variables 1, 2 such that . . . Learn the Central Limit Theorem , which states that the sample mean follows an approximate normal distribution regardless of the underlying distribution. See examples, implications and applications of the theorem with simulation and R code.
