The Central Limit Theorem (CLT) is a core idea in statistics which says that when we repeatedly sample independent and identically distributed random variables, the distribution of their averages will approach a normal distribution as the sample size grows - no matter what the original data distribution looks like. This can be visualized with the classic ball-and-peg example from the video. As each ball lands in a final position, the collection of outcomes gradually forms a bell-shaped curve, be
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The Central Limit Theorem (CLT) is a core idea in statistics which says that when we repeatedly sample independent and identically distributed random variables, the distribution of their averages will approach a normal distribution as the sample size grows - no matter what the original data distribution looks like. This can be visualized with the classic ball-and-peg example from the video. As each ball lands in a final position, the collection of outcomes gradually forms a bell-shaped curve, be
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