You are trying to decide whether to take Stat 200 as an on-line or face-to-face class, but you don't know if you can stay awake through an in-class,...

You are trying to decide whether to take Stat 200 as an on-line or face-to-face class, but you don’t know if you can stay awake through an in-class, 2-hour (120- minute) lecture. 

As a test you decide to audit a session of a current f2f Stat 200 class to see how it goes. You note that there is coffee available before the lecture begins and that fifteen (15) out of the 30 students in this class drink a cup. So, you decide to observe those 15 students and note how long each of these coffee drinkers stays awake. (this is NOT a particularly random sample, hence the results are not that reliable, but they will be interesting). 

Here are the times (in minutes) that each of these 15 coffee drinking students was able to stay awake:

30, 60, 45, 80, -5 (fell asleep before the lecture even started), 90, 100, 90, 115, 120, 80, 100, 80, 80, 100

After the lecture you decide that If you can stay awake for at least _____ (pick a number) of the 120 minutes the lecture lasts, you will get enough out of it to pass the course (this may be a bad criterion, but it’s the one you have decided to use). 

OK, now what statistical analysis do you perform on this data? Let’s go with CONFIDENCE INTERVALS. Explain why this is a good method and then CALCULATE a CONFIDENCE INTERVAL of your choice (50%, 75%, 89%, etc.)  for the time these 15 coffee drinkers can stay awake on average. Is the number of minutes you decided on being awake IN THAT CONFIDENCE INTERVAL? Will you be drinking coffee before the lectures?

Bottom line: Is coffee the key to success in a f2f Stat 200 class? (Would it help in our on-line course?)

FINALLY, what are some of the flaws in this observational analysis? How might it be better designed?