Answer: A symmetric distribution.

### Explanation **Correct Answer: B** The central limit theorem (CLT) states that, for a sufficiently large sample size, the sampling distribution of the sample mean will approximate a normal distribution, regardless of the population's underlying distribution. The normal distribution is symmetric (skewness = 0). - **Option A (Incorrect):** The underlying binomial distribution may exhibit skewness when the probability of success (p) is not 0.5, but the CLT ensures the sampling distribution of the sample mean becomes symmetric as the sample size increases. - **Option B (Correct):** The CLT guarantees that the sampling distribution of the sample mean will be approximately normal (and thus symmetric) for large sample sizes, given the population has a finite variance. - **Option C (Incorrect):** Similar to Option A, this confuses the skewness of the underlying binomial distribution with the symmetry of the sampling distribution of the sample mean under the CLT. **Key Takeaway:** The CLT is fundamental in statistics as it justifies the use of normal distribution-based methods for inference about the sample mean, even when the population distribution is non-normal.

Author: LeetQuiz Editorial Team