A distribution is what the data looks like (to put it in very simplified terms). Distributions can either be discrete (exact values) or continuous (infinite decimal values). When we simulate a distribution, the center of the distribution/highest peak becomes known as the expected value of the distribution. This means that, given no other information, we'd expect a random trial to give us that value because it is the most common.
A uniform distribution is one where the probability of any value happening is the same throughout the distribution. Remember that the the probability under a curve (uniform or not) is always equal to 1. We did the following example of a uniform distribution in class on Friday but never quite got around to finishing it. Click on the link below to get the whole video solution to the following question:
"Let x be the time in minutes that a commuter must wait for a public transit train, with the minimum wait time being 0 minutes and the maximum wait time being 20 minutes. Suppose that the writ times are uniformly distributed.
A. Draw a density curve to model the distribution.
B. what is the probability that x is less than 10 minutes?
C. What is the probability that x is between 7 and 12 minutes?
D. Find the value of c for which P(x < c) = .9.
http://www.educreations.com/lesson/view/uniform-distribution/13711048/?s=LDKaL9&ref=app
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