The sampling distribution of the sample mean approaches a normal distribution as the sample size gets larger, no matter what is the shape of the population distribution.
The above statement is:
Answer & explanation
Correct answer: option 2
The correct answer is Option (2) → Central limit theorem
This is the central limit theorem: for a large sample size n (in practice n ≥ 30), the distribution of the sample mean \( \bar{x} \) is approximately normal with mean \( \mu \) and standard deviation \( \frac{\sigma}{\sqrt{n}} \), whatever the shape of the population distribution.
CBSE Applied Mathematics (Class XII):
Central Limit Theorem
