Which of the following statements best describes the Central Limit Theorem (CLT) and its implications in statistics?

a) The Central Limit Theorem states that the distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the population’s distribution, provided the population has a finite mean and variance.
b) The Central Limit Theorem states that the population distribution will always be normal if the sample mean is normally distributed, regardless of the sample size.
c) The Central Limit Theorem applies only to data that is originally normally distributed and does not hold for data with other distributions.
d) The Central Limit Theorem states that as the sample size increases, the variance of the sample mean increases and diverges from the population variance.