(Solved): 1. When analyzing a sample drawn from the population, what are the benefits of having a large sample ...

1. When analyzing a sample drawn from the population, what are the benefits of having a large sample? [Select three (3) options]

2. What is the difference between a sampling distribution of the means and a sample distribution?

• A. A sample distribution CANNOT be calculated whereas a sampling distribution of the means CAN be calculated.
• B. A sample distribution is used to estimate the population whereas a sampling distribution of the means is used to estimate each sample statistic.
• C. A sample distribution describes the distribution of a single sample whereas a sampling distribution of the means describes the distribution of many sample means taken from the population.
• D. A sample distribution is normally distributed, but a sampling distribution of the means is positively skewed.

3. What is the relationship between a sampling distribution of the means and a sample distribution?

• A. A sampling distribution of the means is always wider than the sample distribution.
• B. The sampling distribution of the means is always equal to the sample distribution.
• C. The sampling distribution of the means is always smaller than the sample distribution.
• D. A sampling distribution of the means is unrelated to the sample distribution.

 4. What is the importance of the Central Limit Theorem?

• A. The sample statistics accurately estimate the population statistics.
• B. Researchers should draw a sample from the center of the population distribution to be confident in their conclusions.
• C. With a large enough sample, the sample distribution will be symmetrical around the mean.
• D. The middle value of a sample equals the population mean