To begin, open "Binomial distribution"

https://media.pearsoncmg.com/cmg/pmmg_mml_shared/animations/statistics/west_applets_HTML5/binomialdemo.html

Setn=60 andp=0.167.

a) SetN=1 and click "Simulate". This should result in a single bar appearing indicating the number of 6's that were rolled out of the 60 rolls. Roll the cursor over the bar to see how many successful "Outcomes" occurred.

How many 6's were rolled? Does this outcome seem unusual? Explain.

b) Click "Simulate" again. Again, a single bar should appear.

How many 6's were rolled this time? Does this outcome seem unusual? Explain

c) Now, setN=10 and click "Simulate". (You just repeated the "roll a die 60 times" experiment 10 times.) This should result in multiple bars appearing, perhaps of varying heights. For each bar, the "Outcomes" is how many 6's (out of 60 rolls) were rolled and the "Count" is how many of the 10 repetitions of the experiment had that same outcome.

What was the fewest number of 6's rolled in these 10 repetitions of the experiment?

What was the greatest number of 6's rolled in in these 10 repetitions of the experiment?

What was the most common number of 6's rolled (if any) in the 10 repetitions of the experiment?No common numbers of 6's rolled? For how many of the 10 repetitions were that many 6's rolled?

d) SetN=1000 and click "Simulate". Again, there should be multiple bars of varying heights.

Describe the shape of the distribution.

What was the most common number of 6's rolled in the 1000 repetitions of the experiment? Does this match what is expected for a fair die? Explain.

How many times out of the 1000 repetitions were that many 6's rolled?

What was the greatest number of 6's rolled (out of 60) in the 1000 repetitions of the experiment?