Probability formulas and examples
[DOC File]SOME STATISTICS FORMULAS
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PROBABILITY FORMULAS Probability of an event A. where f = frequency of occurrence of event n = sample size Probability of the complement of event A. P(not A) = 1 - P(A) Multiplication rule for independent events. General multiplication rules Addition rule for mutually exclusive events. P(A or B) = P(A) + P(B) General addition rule
[DOC File]RANDOM VARIABLES: probability distributions, means, …
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RANDOM VARIABLES: probability distributions, means, variances. Random Variable = Numeric outcome of a random phenomenon. Discrete example: Consider a bag of 5 balls numbered 3,3,4,9, and 11. Take a ball out at random and note the number and call it X, X is a random variable. Let’s complete the probability distribution of X.
[DOC File]SETTING UP A PROBABILITY TABLE
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Second, it is easy to forget that the probability that you divide by, P(B), must be the probability of the condition (the event after the bar) in the conditional probability. With a probability table, a conditional probability is always computed by dividing an intersection (inner) probability by a marginal (outer) probability. Examples: 1.
[DOC File]Suppose that a pair of random variables have the same ...
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By using the following examples, the joint probability mass function for two discrete random variables and their properties, their marginal probability mass functions, the case for independent and dependent variables, their conditional distributions, expected value, variance, covariance, and correlation will …
[DOC File]PROBABILITY AND EXPECTED VALUE - Fulshear, Texas
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The probability of the event is a measure of how likely that the statement will be true in a randomly selected trial; the more likely the event, the higher the probability. In 291, we’ll need three computational formulas for evaluating probability. Before we develop them, though, we need some notation. Notation
[DOC File]Probability
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What is the probability that John arrives no later than 8:10? Suppose we let T be the time in minutes past 8:00 that John arrives. Then the probability density function is given by f(t) = 1/30 for 0 ( t ( 30 and f(t) = 0 for other values of t. The probability that John arrives no later than 8:10 is …
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