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15: Random Selection

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    • 15.1: Random Selection
      This page introduces random sums with a counting variable \(N\), independent cases, and applications in customer demand and service times. It details mean and variance calculations for compound demand, utilizing generating functions and providing examples. The text also covers probability distributions, including generating functions and approximations for both integer and non-integer outcomes.
    • 15.2: Some Random Selection Problems
      This page covers various statistical concepts, including Random Selection in multinomial trials, extreme values of iid random variables, and Bernoulli trials. It explains the relationship between Poisson distributions and multinomial trials, derivations of minimum and maximum values in sample distributions, and generating functions for counting processes.
    • 15.3: Problems on Random Selection
      This page contains a collection of exercises centered on probability distributions, including binomial, Poisson, and exponential distributions. The exercises explore various scenarios involving dice rolls, coin flips, customer behaviors, and statistical calculations like expected values and variances. Key topics include determining probabilities for events such as sales, questionnaire responses, and errors in data transmission.

    This page titled 15: Random Selection was last modified on Sun, 25 Oct 2026 20:34:13 GMT and is shared under a CC BY 3.0 license and was authored, remixed, and/or curated by Paul Pfeiffer via source content that was edited to the style and standards of the LibreTexts platform.