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<title>Monografías / Capítulos de monografía Q&amp;C</title>
<link href="https://hdl.handle.net/10259/11247" rel="alternate"/>
<subtitle/>
<id>https://hdl.handle.net/10259/11247</id>
<updated>2026-05-24T14:55:30Z</updated>
<dc:date>2026-05-24T14:55:30Z</dc:date>
<entry>
<title>Quality of Analytical Measurements: Statistical Methods for Internal Validation</title>
<link href="https://hdl.handle.net/10259/11248" rel="alternate"/>
<author>
<name>Ortiz Fernández, Mª Cruz</name>
</author>
<author>
<name>Sarabia Peinador, Luis Antonio</name>
</author>
<author>
<name>Sánchez Pastor, Mª Sagrario</name>
</author>
<author>
<name>Herrero Gutiérrez, Ana</name>
</author>
<id>https://hdl.handle.net/10259/11248</id>
<updated>2026-01-21T01:05:44Z</updated>
<published>2020-01-01T00:00:00Z</published>
<summary type="text">Quality of Analytical Measurements: Statistical Methods for Internal Validation
Ortiz Fernández, Mª Cruz; Sarabia Peinador, Luis Antonio; Sánchez Pastor, Mª Sagrario; Herrero Gutiérrez, Ana
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.
</summary>
<dc:date>2020-01-01T00:00:00Z</dc:date>
</entry>
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