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Money data

Speaking of "money" data, there are many talks about sales, stocks, prices, but here I considered the nature of money as data.

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Analogy with frequency data

Money may have a negative number in the calculation, but basically there are only integers greater than or equal to 0.

Also, the total value of money is meaningful.

These properties will be the same as the frequency data in statistics, so I think it makes sense to treat money data in the theory of frequency data. These theories include crosstabs and correspondence analysis .

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Distinguishing data by "total value is meaningful or not"

The method of classifying data on the measurement page is well known. On the other hand, it is not common to distinguish data based on whether the total value makes sense.

Both "temperature" and "length" are characterized by "quantitative data", "continuous data", and "measurement data". Regarding "temperature", the total of "20 degree + 25 degree = 45 degree" is physically wrong, and there is no point in calculating the total value. The sum of "lengths" is used as "lengths".

When derailed, temperature does not sum, but "energy", which is closely related to temperature, is a meaningful amount to sum. I have never heard of the use of these properties as a data scientist's skill, but I think that energy engineers use it without being particularly conscious of it.

"Frequency" and "money" can be treated as "discrete data" and "counting data", but totals are calculated on a daily basis.

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