Instead of rolling a die 100 times, use StatCrunch to simulate 100 rolls of a die. Use StatCrunch to create a random generators to produce the whole numbers 1, 2, 3, 4, 5, 6 randomly. (Select Data, then Simulate Data, then Uniform. By Rows: type 100 (actually, any number larger than your population size). By columns: type 1. For a, enter 1, and for b, enter 6. Select simulate. A new column of data will appear, with numbers in random order.)
Now, construct and display a histogram of the sample means.
Without actually generating a histogram of 5000 rolls, what would you expect the shape of 5000 simulated roll of a die to be? How does that compare to the histogram you just created of the 100 sample means? Explain the following in your own words:
• How does the mean of the 100 sample means compare to the mean of many rolls of a fair die?
• How does the standard deviation of the sample means compare to the standard deviation of outcomes when a single die is rolled a large number of times?
• How do these results demonstrate the Central Limit Theorem? Explain in your own words using you own results. Be specific and clear.