Abstract
Basic concepts of hypothesis testing are presented in this Chapter. The Neyman-Pearson Lemma, which gives the form of the Most Powerful test for simple hypotheses, is introduced. This is then used as the building block for constructing the Uniformly Most Powerful tests and the Uniformly Most Powerful Unbiased tests. In this connection, special assumptions on the forms of the distribution of the data, such as the Monotone Likelihood Ratio, are presented. The focus is on testing of a scalar parameter.
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Li, B., Babu, G.J. (2019). Testing Hypotheses for a Single Parameter. In: A Graduate Course on Statistical Inference. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-9761-9_3
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DOI: https://doi.org/10.1007/978-1-4939-9761-9_3
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