2026-06-17T21:33:07Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112482026-01-21T01:05:44Zcom_10259_4249com_10259_5086com_10259_2604col_10259_11247

Quality of Analytical Measurements: Statistical Methods for Internal Validation Ortiz Fernández, Mª Cruz Sarabia Peinador, Luis Antonio Sánchez Pastor, Mª Sagrario Herrero Gutiérrez, Ana Analysis of variance (fixed or random effects model) Confidence and tolerance intervals Fit for purpose Power of a hypothesis test Any aspect of the contemporary social activity is somehow supported in the analytical measurements. The cost of these measurements is high, but the cost of the decisions made based on incorrect results is much greater. For example, a test that wrongly shows the presence of a forbidden substance in a food destined for human consumption can result in an expensive claim. Thus, it is important to provide a correct result, but it is equally important to be able to prove that the result is correct. This article focuses on statistical evaluation of data in the context of validation of a method to show what information can, or cannot, be extracted from the experimental results. 2026-01-20T11:56:30Z 2026-01-20T11:56:30Z 2026-01-20T11:56:30Z 2020 info:eu-repo/semantics/bookPart 978-0-444-64166-3 https://hdl.handle.net/10259/11248 10.1016/B978-0-12-409547-2.14746-8 eng Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, p. 1-52 https://doi.org/10.1016/B978-0-12-409547-2.14746-8 info:eu-repo/semantics/closedAccess Elsevier