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8: Set Estimation

  • Page ID
    10199
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    Set estimation refers to the process of constructing a subset of the parameter space, based on observed data from a probability distribution. The subset will contain the true value of the parameter with a specified confidence level. In this chapter, we explore the basic method of set estimation using pivot variables. We study set estimation in some of the most important models: the single variable normal model, the two-variable normal model, and the Bernoulli model.


    8: Set Estimation is shared under a CC BY 2.0 license and was authored, remixed, and/or curated by Kyle Siegrist via source content that was edited to conform to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.