MGMT 1050 Lecture Notes - Lecture 3: New South Wales Xpt
20 Jul 2016
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Bayes theorem explained with an example: marshall. Let"s suppose that 20% of the students in a class are having trouble with a statistical add-in for excel and the rest are not. Let p(t) be the probability that students are having problem with the add-in. The incidence of this problem seems to be related to using windows xp. Let p(xp) be the probability of using windows xp. Suppose that we know that 75% of the people reporting the problem are using windows xp and that 60% of the class is using xp. We know: p(t) = 0. 2, p(xp) = 0. 60 and p(xp|t) = 0. 75. Suppose we want to know the probability that an xp user is having trouble with the add-in, p(t|xp). P(t) and p(xp) are unconditional or marginal probabilities, which we can enter on our table as follows: The organization of the table is not important.
