Abstract
Measurement uncertainties may arise from different sources, and certain sources of error may not be accounted for in the initial error budget. The presence of unreported sources of uncertainty may sometimes lead to a poor goodness-of-fit statistic and the rejection of the model used to fit the data. These missing sources of uncertainty may either be associated with the data themselves or with the model used to describe the data. In both cases, it is possible to account for these errors and thus ensure that the hypothesis testing is not biased by them.
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Bonamente, M. (2022). Systematic Errors and Intrinsic Scatter. In: Statistics and Analysis of Scientific Data. Graduate Texts in Physics. Springer, Singapore. https://doi.org/10.1007/978-981-19-0365-6_17
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DOI: https://doi.org/10.1007/978-981-19-0365-6_17
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Online ISBN: 978-981-19-0365-6
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