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 ten 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 90 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 the 90% and 95% confidence intervals for the time these 15 coffee drinkers can stay awake on average.
Bottom line: Is coffee the key to success in a f2f Stat 200 class? (Would it be necessary in our on-line course?)
FINALLY, what are some of the flaws in this observational analysis? How might it be better designed?