Working with spectral and chromatographical data often results in noisy data. The good news is, there is a simple and efficient way to extract the signals from the noise, enabling a deeper and better understanding of processes and products. 

If you are working on product or process development problems, you might need to utilise spectral and chromatographic data to understand and confirm that the process is performing optimally and generates the desired product. Often, we may summarise these data by using estimates based on peak height, position, and shape. But using these summaries inevitably causes us to lose some information about our process. This can reduce the insights we gain from our data analysis process and can negatively impact the quality of our decisions.

Spectral and related data are inherently noisy. This webinar will present a simple and efficient way of extracting the signals from the noise for a deeper, better understanding of your processes and products. If you are a scientist or engineer collecting spectral, chromatographic, or similar data and want to gain deeper insight into the trends and outcomes, this webinar is for you.


Stuart Little

Stuart Little is a Systems Engineer at JMP,  where he applies a background in the chemicals industry to helping provide solutions to a broad range of data and statistical problems. He has previously been Lead Research Scientist at Croda, a chemical products manufacturer. Stuart holds a Phd in Chemistry from the University of Sheffield.

Register now for this free webinar.

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