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Outliers #9

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ryannjones opened this issue Oct 30, 2014 · 0 comments
Open

Outliers #9

ryannjones opened this issue Oct 30, 2014 · 0 comments
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Description of Error: Data can have legit outliers, but sometimes it's more nefarious. Check yourself before you wreck yourself.

Things to look for: Sort or order all applicable fields. Double-check the veracity of any super-high or super-low numbers. Call to confirm with your data source if needed. Related: are there any negative values? This can indicate an import or calculation error. Calculate average and standard deviation of fields and inspect any values that aren't within two or three standard deviations.

Examples:
@ryannjones ryannjones self-assigned this Oct 30, 2014
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