How does the sample size impact the accuracy of the Central Limit Theorem?
- As the sample size increases, the approximation of the sample mean to a normal distribution becomes more accurate.
- Sample size has no impact on the Central Limit Theorem.
- The Central Limit Theorem becomes less accurate as the sample size increases.
- The Central Limit Theorem is only accurate when the sample size is exactly 30.
According to the Central Limit Theorem, as the sample size increases, the distribution of the sample mean approaches a normal distribution more closely. This means the larger the sample size, the more accurately the sample mean will represent a normal distribution.
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