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This page is a page of data science for environment and quality . The word "diversity" is commonly spoken of as "biodiversity" or "diversity of human personality", which are more related to the "environment".

On the other hand, "quality" is not called "diversity", but "high-mix low-volume production" is an important issue. High-mix low-volume production is about product diversity.

Therefore, diversity is an important point in both "environment" and "quality".

Data Science for Diversity

When "diversity" is spoken, there is a difference in the content from a data science perspective. If you are aware of this difference, it seems easy to think about how to deal with it.

Diversity = magnitude of variability within one variable

The greater the variability, the more diverse it is considered.

Even if we say "variation" in a nutshell, the properties that can be handled differ between quantitative variables and qualitative variables.

Diversity = number of variables

A "variable" can also be called a "scale of evaluation". With this a lot, you will be able to evaluate different aspects of things.

However, in reality, the story does not proceed with such tabular data, some samples have only "A, B" data, and some samples are "C, D". Sometimes it seems like you only have the data. Also, the fact that the variables that are important to each of the two people are different can be the cause of the disagreement. People say, "The ruler is different."

The history of the study of diversity

Around 2010, "diversity" was almost "biodiversity". Around this time, the so-called "eco" was popular, and many biodiversity manuals were published. There is also biodiversity economics .

From around 2020, the topic of "human diversity" has been increasing.

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