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terrykrohe OP t1_j27j6ge wrote

Reply to comment by Frogmarsh in [OC] best-fit lines, correlations: missing persons vs 'rural-urban' – 2020 election by terrykrohe

... the t-test (0.96) quantifies only the missing persons Rep and Dem data

... there is no t-test reported for the 'rural-urban' metric: it would be very small because the means are very different)

... the point is that missing persons data is very different in character than the data of other metrics (e.g. 'rural-urban' is shown here, but GDP and others were posted previously would be similar to 'real-urban')

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Frogmarsh t1_j27jrzf wrote

What is the upper right plot?

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terrykrohe OP t1_j27z5ou wrote

... the upper right plot shows the 'rural-urban' values of the fifty states, ranked from more rural to more urban. This uses a definition described in the "sources" comment below.

... the bottom plot relates the top two plots: for each state its ('rural-urban', missing persons) coordinate is plotted. Is there a relationship? Do more missing persons come rural or urban states? The plot indicates that there is little (essentially none) relationship: tell me a state's 'rural-urban' value and I cannot tell you anything about that state's missing persons.

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Frogmarsh t1_j29my6n wrote

So, those upper plots do not accompany a t-test?

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terrykrohe OP t1_j2a47t4 wrote

from "sources" comment below:

Missing persons and 'rural-urban' metrics: note that missing persons t-test indicates that data fluctuations are probably "random" in character. (t-test = 0.96)
The large difference of 'rural-urban' means (> 1 SD) for Rep and Dem states indicate that Rep and Dem states are different Sample populations. (un-reported t-test = 0.000126)

more about the t-test:
https://en.wikipedia.org/wiki/Student%27s_t-test

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Frogmarsh t1_j2acvs7 wrote

I’m guessing English isn’t your first language.

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