Large sample approximation refers to the statistical concept that, as the size of a sample increases, the distribution of the sample mean will approach a normal distribution regardless of the shape of the population distribution. This is closely linked to the Central Limit Theorem, which states that for sufficiently large samples, the means of random samples will tend to be normally distributed, allowing for easier analysis and interpretation of data.
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