Handout17-Statistics2

Handout17-Statistics2 - CEM 834 STATISTICS FALL 2005 II....

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CEM 834 STATISTICS FALL 2005 II. Probability Distribution Functions In this section, we shall consider some important probability distribution functions. These functions represent a model for the experimental data or system of interest. The model may be good or bad, depending on the validity of the assumptions on which the model is predicated. Therefore, it is necessary to understand the assumptions in order to determine under what conditions the model is an exact description of the experimental system and under what conditions it is a reasonable approximation. It is also of interest to determine the properties of the various probability distribution functions and how calculations may be performed with them. A. Binomial Distribution Consider an experiment in which only two outcomes are possible, one that we shall call a success and the other that we shall call a failure. The probability for success in an individual experiment or trial is p, and the probability for failure is q 1 p = - . For a series of n mutually independent trials, the overall probability of observing x successes and n x - failures is x n x ) p 1 ( p ! ) x n
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This note was uploaded on 07/25/2008 for the course CEM 834 taught by Professor Mcguffin during the Fall '05 term at Michigan State University.

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Handout17-Statistics2 - CEM 834 STATISTICS FALL 2005 II....

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