On a highway, the Average Waiting time for a cop for stopping a car is 10 min. The waiting time T is measured in hours and is an exponential random variable. What is the total amount of waiting time before a 4th car is stopped? What is the standard deviation of the total amount of time until the 4th car is stopped? What is the probability that the cop will have to wait more than 40 minutes before stopping the 4th car?
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!
On a highway, the Average Waiting time for a cop for stopping a car is 10 min. The waiting time T is measured in hours and is an exponential random variable.
What is the total amount of waiting time before a 4th car is stopped?
What is the standard deviation of the total amount of time until the 4th car is stopped?
What is the probability that the cop will have to wait more than 40 minutes before stopping the 4th car?
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