A researcher takes 10 samples of 20 students each to get a sampling distribution of the average number of siblings students at a university have. According to the Central Limit Theorem, what can the researcher do make their sampling distribution get closer to normal?

• A. Increase the number of samples
• B. Increase the sample size
• C. Decrease sample size
• D. Decrease number of samples

Answer: (B)

Verified step by step guidance

1. Step 1: Understand the Central Limit Theorem (CLT). The CLT states that as the sample size increases, the sampling distribution of the sample mean becomes approximately normal, regardless of the population's original distribution.
2. Step 2: Identify the factors that influence the normality of the sampling distribution. These include the sample size and the number of samples taken.
3. Step 3: To make the sampling distribution closer to normal, the researcher can increase the sample size. Larger sample sizes reduce variability and make the sampling distribution more normal.
4. Step 4: Another way to improve the normality of the sampling distribution is to increase the number of samples. More samples provide a better representation of the population and improve the accuracy of the sampling distribution.
5. Step 5: Avoid decreasing the sample size or the number of samples, as these actions would reduce the reliability and normality of the sampling distribution.