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9: Independent Classes of Random Variables

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    • 9.1: Independent Classes of Random Variables
      This page covers the concept of independence for random variables, extending it from events to pairs \{X, Y\}, and defines independence through events generated by these variables. It illustrates marginal and joint probabilities, emphasizing not all normally distributed pairs are jointly normal. The use of MATLAB functions (icalc, itest, etc.) is demonstrated for calculating joint probabilities and testing independence, including practical examples with joint distributions.
    • 9.2: Problems on Independent Classes of Random Variables
      This page provides exercises centered on the independence of pairs of random variables, utilizing joint distributions to assess their relationships. Topics include analyzing joint probability matrices, calculating probabilities in scenarios like software completion times and sales opportunities, and applying various distribution types (e.g., binomial, exponential) in problem-solving contexts.

    This page titled 9: Independent Classes of Random Variables 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.