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Explanation: The Central Limit Theorem (CLT) states that, regardless of the shape of the population distribution , the distribution of sample means will tend to be normal (bell-shaped) if the sample size is sufficiently large (typically n ≥ 30 ). Here, despite the right-skewed nature of the claim amounts , the repeated sampling process ensures that the sample means approximate a normal distribution , allowing for reliable statistical inferences.
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