A subway train on the Red Line arrives every 7 minutes during rush hour. We are interested in the length of time a commuter must wait for a train to arrive. The time follows a uniform distribution.Give the distribution of X. find . f(X) = , where ≤ X≤
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!
A subway train on the Red Line arrives every 7 minutes during rush hour. We are interested in the length of time a commuter must wait for a train to arrive. The time follows a uniform distribution.Give the distribution of X. find .
| f(X) | = |
|
, where ≤ X≤ |
. μ =
σ =
Find the probability that the commuter waits less than one minute. (Enter your answer as a fraction
Find the probability that the commuter waits between two and three minutes.
State "60% of commuters wait more than how long for the train?" in a probability question. (Enter your answer to one decimal place.)
Draw the picture and find the probability. (Enter your answer to one decimal place.)
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