Amortized Time vs. …
Contrasting Amortized Time
Suppose you're thinking about doing some volunteer work in the community for ten weeks over the summer. There are several projects you could work on, and they each one has different time commitments:
- Worst-Case Kitchen: Maximum of 5 hours per week, every week.
- Amortization Park: At the end of week \( m \) you'll have done at most \( 4m \) hours of work, with a maximum of 40 hours total over the ten-week period.
- Expectation Center: Each week varies, but it averages out to be 4.5 hours per week, with a 1-hour standard deviation.
Amortization Park's promise is that by the end of week 9, you will have done at most 36 hours of work. If the previous weeks each only asked you to work two hours, you'll only have done 16 hours by week 9, so during week 9 you could be asked to work for 20 hours (i.e., \( 36 - 16 \) hours).
Both worst-case time and amortized time provide a hard guarantee about the total amount of time you'll spend working over the summer: 50 hours at the Worst-Case Kitchen and 40 hours at Amortization Park. Unfortunately, 50 hours is too many.
Assuming a normal distribution, there is a 82.9% chance that volunteering at the Expectation Center will take less time than your 48-hour limit, but there's also a 17.1% chance that it will take longer.
So it seems like your best choice is Amortization Park, followed by the Expectation Center, and then the Worst-Case Kitchen.
People often overestimate the chance of unlikely events. Assuming a normal distribution with a mean of 4.5 and a standard deviation of 1 for each week's work, the mean for the sum of ten samples is 45, with a standard deviation of \( \sqrt{10} \). So 60 hours would be 4.75 standard deviations away from the mean. That's really unlikely, with a chance of about 1 in a million.
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