Abstract
A rigorous and precise determination of uncertainty intervals for frequentist estimates requires the evaluation of confidence intervals with the proper probabilistic content, called coverage in this context. The Neyman procedure is introduced, and its results are discussed in particular in the case of discrete random observable variable, where the exact coverage cannot be ensured. The binomial interval determination due to Clopper and Pearson is presented as concrete case. The flip-flopping problem and the unified approach, due to Feldman and Cousins, are introduced.
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References
J. Neyman, Outline of a theory of statistical estimation based on the classical theory of probability. Philos. Trans. R. Soc. Lond. A Math. Phys. Sci. 236, 333–380 (1937)
C.J. Clopper, E. Pearson, The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26, 404–413 (1934)
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Lista, L. (2023). Confidence Intervals. In: Statistical Methods for Data Analysis. Lecture Notes in Physics, vol 1010. Springer, Cham. https://doi.org/10.1007/978-3-031-19934-9_8
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DOI: https://doi.org/10.1007/978-3-031-19934-9_8
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