1 4. Discrete Probability Distributions 4.1. Random Variables and Their Probability Distributions Most of the experiments we encounter generate outcomes that can be interpreted in terms of real numbers, such as heights of children, numbers of voters...
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1 4. Discrete Probability Distributions 4.1. Random Variables and Their Probability Distributions Most of the experiments we encounter generate outcomes that can be interpreted in terms of real numbers, such as heights of children, numbers of voters favoring various candidates, tensile strength of wires, and numbers of accidents at specified intersections. These numerical outcomes, whose values can change from experiment to experiment, are called random variables. We will look at an illustrative example of a random variable before we attempt a more formal definition. A section of an electrical circuit has two relays, numbered 1 and 2, operating in parallel. The current will flow when a switch is thrown if either one or both of the relays close. The probability that a relay will close properly is 0.8, and the probability is the same for each relay. The relays operate independently, we assume. Let Ei denote the event that relay i closes properly when the switch is thrown. Then P(Ei) = 0.
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