The statement is false. A sampling distribution is normal if either n > 30 or the population is normal.
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Explanation:
If the underlying population is normally distributed, then so is the sample distribution (such as the distribution of sample means, aka xbar distribution).
Even if the population isn't normally distributed, the xbar distribution is approximately normal if n > 30 due to the central limit theorem. Some textbooks may use a higher value than 30, but after some threshold is met is when the xbar distribution is effectively "normal".
Choice A is close, but is missing the part about the population being normal. If we know the population is normal, then n > 30 doesn't have to be required.
