Dissecting random and systematic differences between noisy composite data sets

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Dissecting random and systematic differences between noisy composite data sets

Composite data sets measured on different objects are usually affected by random errors, but may also be influenced by systematic (genuine) differences in the objects themselves, or the experimental conditions. If the individual measurements forming each data set are quantitative and approximately normally distributed, a correlation coefficient is often used to compare data sets. However, the r...

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ژورنال

عنوان ژورنال: Acta Crystallographica Section D Structural Biology

سال: 2017

ISSN: 2059-7983

DOI: 10.1107/s2059798317000699