The time required to complete a marathon run is normally distributed with a mean of 360 minutes and a standard deviation of 15 minutes. a) what is the maximum number of minutes that the fastest 15% of runners will take to finish the race? b) what is the least number of minutes that the slowest 15% will take to finish the race?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
The time required to complete a marathon run is
- a) what is the maximum number of minutes that the fastest 15% of runners will take to finish the race?
- b) what is the least number of minutes that the slowest 15% will take to finish the race?
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