The central limit theorem says that the sum of a group of independent, identically distributed random variables approaches a distribution as the number of random variables increases.
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Independent random variables are those whose outcomes do not affect each other. For example, the result of rolling one die does not influence the result of rolling another die. Show more…
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The Central Limit Theorem states that a sum of independent, identically distributed random variables is equal to a normal random variable. True False
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The Central Limit Theorem states that "if a sample of size n is drawn from any random variable that has a mean (μ) and a standard deviation (σ), then the distribution of the sample mean approaches a normal distribution with mean (μ) and standard deviation (σ/√n) as the sample size, n, increases." Explain why the Central Limit Theorem is important in Statistics.
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