Level: Beginner
【Presenter】
Laura Higgins, JMP Global Technical Enablement Engineer, JMP, SAS Institute Inc.
[Announcement summary]
JMP 16's Design of Experiments platform has a new feature that incorporates detection limits into column properties, which are automatically applied during modeling with JMP Pro's Generalized Regression. We will demonstrate these new features and explain the impact of detection limits on data analysis.
When looking for a very small amount of substance, there are limits depending on the technology used. The lower limit of detection is the fact that a substance is not detected even if it is present, but when detecting a small amount of substance in important situations such as identifying the onset of an infectious disease or correctly identifying a small amount of impurities. It has a very important meaning.
Ignoring detection limits in data analysis can have serious implications, such as biasing basic statistics such as mean values and confidence intervals, which can be misleading. Also, if you model your data under the wrong assumptions about the detection limit, you will end up with the wrong model. And this detection limit affects industrial applications such as pharmaceutical and chemical manufacturing, analytical chemistry, and diagnostic test design.
* Play the video on this site, click "CC" at the bottom right of the screen, and select "English" to display English subtitles.
If you would like to download the presentation materials and data of this announcement, or watch them together with the Japanese transcript, Here Please click on the.
Go to the page for each presentation in the Discovery Summit Americas 2021 Presentation.
(Please note that you will be asked to log in to SAS Profile.)
