According to the Central Limit Theorem multiple choice sample size is important when the population is not normally distributed increasing the sample size decreases the dispersion of the sampling distribution the sampling distribution of the sample means is uniform the sampling distribution of the sample means will be skewed

The answer is "Sample size is important when the population is not normally distributed ".

Step-by-step explanation:

The theorem for the central limit indicates that perhaps the sample distribution of means by the sample is close to the confidence interval independent of the underlying population demographics when large samples are derived from every population, with and confidence interval . The bigger the sample, the stronger the approach (typically ). The sample is therefore significant unless the population is not typically spread.