Answer :
The Central Limit Theorem states that over a large number of samples, the sampling average of the sample means would be closer to the population mean.
What does the Central Limit Theorem state?
The Central Limit Theorem states that for a random variable X, with mean given by [tex]\mu[/tex] and standard deviation given by [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
This means that over a large number of trials, i.e., of samples from the population, the mean of the sample means will be close to the population mean, with a small standard error, as the standard error is inversely proportional to the square root of the sample size.
More can be learned about the Central Limit Theorem at https://brainly.com/question/25800303
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