Question
what does the central limit theorem state about the sampling distribution of the sample means? A. The sampling distribution of sample means is uniform B. The sampling distribution of sample means is approximately normally distributed C. The sampling distribution of sample means is skewed D. The sampling distribution of sample means is the same as the population distribution
Answers
GPT-4o mini
The correct answer is **B. The sampling distribution of sample means is approximately normally distributed**.
The Central Limit Theorem states that when you take a sufficiently large number of samples from a population (regardless of the population's distribution), the distribution of the sample means will be approximately normally distributed, provided that the sample size is large enough (commonly n ≥ 30 is suggested). This holds true even if the original population distribution is not normal.
The Central Limit Theorem states that when you take a sufficiently large number of samples from a population (regardless of the population's distribution), the distribution of the sample means will be approximately normally distributed, provided that the sample size is large enough (commonly n ≥ 30 is suggested). This holds true even if the original population distribution is not normal.