Noisy data

Article summary

Noisy data are data that are corrupted, distorted, or have a low signal-to-noise ratio. Improper procedures (or improperly documented procedures) to subtract out the noise in data can lead to a false sense of accuracy or false conclusions. Noisy data are data with a large amount of additional meaningless information in them, known as noise. This includes data corruption and the term is often used as a synonym for corrupt data. It also includes any data that a user system cannot understand and interpret correctly. Many systems, for example, cannot use unstructured text. Noisy data can adversely affect the results of any data analysis and skew conclusions if not handled properly. Statistical analysis is sometimes used to weed the noise out of noisy data.

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1. Summarise the article in your own words. Which single claim would you verify first, and why?
2. Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
3. If two sources disagreed about one of these facts, what would you need in order to trust one over the other?

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