10: Cleaning Up Data — Read — Invisible Network

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When we try to calibrate an analytical method (Chapter 8) or to optimize an analytical system (Chapter 9), our ability to do so successfully is limited by the uncertainty, or noise, in our measurements and by background signals that interfere with our ability to measure the signal of interest to us. In this chapter we will consider ways to clean up our data by decreasing the contribution of noise to our measurements and by correcting for the presence of background signals.

10.1: Signals and Noise
10.2: Improving the Signal-to-Noise Ratio
10.3: Background Removal
10.4: Using R to Clean Up Data
10.5: Exercises

This page titled 10: Cleaning Up Data was last modified on Sun, 06 Jun 2021 15:50:30 GMT and is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by David Harvey.

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