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A spurious relationship is originated by a series of data that offer some sense of correlation that, in practice, is non-existent. The term originates from the word “spurious”, which means “hypothetical”, “not true” or “illegitimate”, for example.

There are also several references to this relationship, which we will explain better throughout the text, as spurious regression. The most important point to understand is that, although these data are indicative, there is actually no conclusion that should really be taken seriously.
The great characteristic of a spurious relationship is its power to deceive those who see it. This is because, statistically, it is possible to build correlations in different data sets that are composed of unit numbers.
However, contrary to what may seem in many cases, there is not always a cause and effect relationship between the variables. Even so, for those who analyze these data sets, they can identify a certain logic, even if false.

When this happens, it is called a spurious relationship. Therefore, it is a series of data and characteristics that, although without any value for those who analyze the data, can generate false interpretations.
I found a very funny spurious correlations in one of the articles that compares an increase in car seat belt results in a lower number of astronaut deaths. One thing has nothing to do with the another which made me laugh and wonder how people can even think about it and compare the facts.