1. With the default setting (uniform population, sample sizes set at 2 and 5, respectively), click the button "5 Samples" a couple of times. Notice how the sample means accumulate at the bottom two graphs. Then click the button "5000 Samples" multiple times until the total number of samples exceeds 50,000. Observe the shape of the two distributions, and compare their variance, skew and kurtosis. Write these numbers down on a piece of paper for future reference. (Square the standard deviation to get the variance).

2. Set the sample sizes to be 10 and 15, respectively. Sample 50,000 times for each sample size. Observe the shape of the two distributions, and compare their variance, skew and kurtosis. Write them down for future reference. Repeat for samples size 25.

3. Review the data you have written down. Answer the following question: How does sample size affect the shape of the sampling distribution of the mean? What is the effect of sample size on the variance. What is the effect on the variance of doubling the sample size (Compare N = 5 to N = 10). What is the effect of tripling the sample size? How does sample size affect skew and kurtosis?

4. Set the population to be "Normal", set the sample size to be 2, 5, 10, 15, 25, respectively. Sample 50,000 times in each case. Write down the variance associated with each sample size on a piece of paper. Does the rule you found with the uniform population hold here?

5. Set the population to be "Skewed" and repeat steps 1-3.

6. Set the population to be "Custom", click and drag mouse in the top graph to construct a distribution of your own., then repeat steps 1-3.