The Central Limit Theorem states that if I have a large number of samples from a
ID: 3438267 • Letter: T
Question
The Central Limit Theorem states that if I have a large number of samples from a population, the means of the samples will form a normal distribution, no matter what the distribution of the original population is. Why is this important?
It allows us to generalize from a sample to a population
It means that all distributions are really normal distributions.
It proves that all samples are good indicators of the population.
It means that researchers can reliably generalize from even very small samples to the full population.
1.It allows us to generalize from a sample to a population
2.It means that all distributions are really normal distributions.
3.It proves that all samples are good indicators of the population.
4.It means that researchers can reliably generalize from even very small samples to the full population.
Explanation / Answer
If the sample size is large enough (greater than 30), we can infer about the population mean by sample mean using the central limit theorem. It does not matter whether underlying population is normal or not as long as sample size is large (greater than 30). So option 1 is correct.
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