%0 Generic %1 bio2020excelling %A BiteSize Bio, %D 2020 %K 62-01-statistics-instructional-exposition 62-04-statistics-explicit-machine-computation-and-programs 62p10-application-of-statistics-to-biology-and-medical-sciences-meta-analysis %T Excelling with Excel: Analytical Method Validation Using LOD and LOQ %U https://bitesizebio.com/48459/excel-lod-loq/ %X When performing an un-established analytical method, one needs to statistically validate it. Failing to do so, you might end up with erroneous results and waste time and resources. Limit of detection (LOD) and limit of quantitation (LOQ) are the two crucial parameters used to validate analytical methods. This article will describe what LOD and LOQ are, their importance in method validation, and finally a quick method to calculate these values using Excel.

@electronic{bio2020excelling, abstract = {When performing an un-established analytical method, one needs to statistically validate it. Failing to do so, you might end up with erroneous results and waste time and resources. Limit of detection (LOD) and limit of quantitation (LOQ) are the two crucial parameters used to validate analytical methods. This article will describe what LOD and LOQ are, their importance in method validation, and finally a quick method to calculate these values using Excel.}, added-at = {2024-04-05T00:41:10.000+0200}, author = {{BiteSize Bio}}, biburl = {https://www.bibsonomy.org/bibtex/21d47f0aea3ce25f9a1ef8a1befed9024/gdmcbain}, interhash = {953bdf2dedd81d3925f7cc975b30bb0b}, intrahash = {1d47f0aea3ce25f9a1ef8a1befed9024}, keywords = {62-01-statistics-instructional-exposition 62-04-statistics-explicit-machine-computation-and-programs 62p10-application-of-statistics-to-biology-and-medical-sciences-meta-analysis}, timestamp = {2024-04-05T00:41:25.000+0200}, title = {Excelling with Excel: Analytical Method Validation Using LOD and LOQ}, url = {https://bitesizebio.com/48459/excel-lod-loq/}, year = 2020 }