Webinar

Analyzing Curve Data with JMP

Learn more about analyzing two types of curves: curves that can be described by a formula and curves that need to be described with a flexible fit. 

Many scientists and engineers have data that are represented by a curve, and using curves in analysis is challenging. Curves are often summarized into a few parameters for analysis. However, parameterizing a curve can be difficult, time-consuming, and most of the data is left behind. In today’s workplace, doing more with less is critical; luckily, JMP can help.

In this webinar, we’ll learn more about analyzing two types of curves: curves that can be described by a formula and curves that need to be described with a flexible fit. 

Examples of curves that can be described with a formula include:

  • dose-response curves
  • enzyme kinetics
  • growth and decay curves
  • pharmacokinetics

Examples of curves that need to be described with a more flexible fit include:

  • complex growth curves
  • chromatograms
  • spectroscopy (NIR, NMR, and Raman)
  • manufacturing sensor data over time

Contact

JMP Statistical Discovery / SAS Institute GmbH

In der Neckarhelle 162
69118 Heidelberg
Germany

+49 (0)6221 415 3367