Abstract
Data often arrives sequentially, rather than as a collection. When this occurs – or when the experiment can be designed so that this occurs – there can be a considerable advantage in using statistical methods, called sequential analysis, that are tailored to such situations. Classical frequentist statistical methods require analysis with a pre-specified collection of data, and hence cannot be used in such sequential settings. Interestingly, Bayesian methods can be directly used in sequential settings.
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Berger, J.O. (2018). Sequential Analysis. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_1295
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DOI: https://doi.org/10.1057/978-1-349-95189-5_1295
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