The time between arrivals of vehicles at a particular intersection follows an exponential probability distribution with a mean of 10 seconds. (a) Sketch this exponential probability distribution. fix) f(x) fix) 0.15 0.15 0.15 0.10 0.10 0.10 0.05 0.05 0.05 5 10 15 20 25 30 10 15 20 25 30 5 10 15 20 25 30 f(x) 0.15 0.10 0.05 5 10 15 20 25 30
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!

![(b) What is the probability that the arrival time between vehicles is 10 seconds or less? (Round your answer to four decimal places.)
[Input box]
(c) What is the probability that the arrival time between vehicles is 6 seconds or less? (Round your answer to four decimal places.)
[Input box with answer: 0.4512 ✔️]
(d) What is the probability of 30 or more seconds between vehicle arrivals? (Round your answer to four decimal places.)
[Input box with answer: 0.0498 ✔️]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9522b0ac-6bb6-4104-840b-2a5d14259dd3%2Fa361a07d-8095-4f07-b42a-32c68ea1f04b%2Fry3tiip_processed.png&w=3840&q=75)
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