Statistically comparing estimates

Hi All,

I've been doing some research on this and I can't seem to find a clear answer.

I want to use 2014-2019 ACS data to see if there is a statistically significant difference in poverty rates between Cook County and the state of Illinois.  So, I would be comparing Illinois as a whole to a smaller part of Illinois.  

I know how to use the Census Bureau's statistical testing tool, but what is the correct method of calculating statistically significant differences?  Is it appropriate to statistically compare two geographic units that overlap a bit?  Or would a better alternative be comparing Cook County to a statewide poverty estimate from which Cook County has been removed?

Any help would be greatly appreciated!

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  • I agree with Mark. It's simple hypothesis testing. "Is subset A significantly different from the total population?" (I think I saw your question the other day about ZCTA, which the same thing applies to.) However, if your subset comprises a very large portion of the population, you might get non-intuitive results. For example, comparing males to the total population. Since the only other option is female, so you may want to divide into two independent samples of male and female. Although there might be statistical vagaries, as a practitioner I would compare two geographic samples that are not independent, so long as the "population" sample is much larger.

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  • I agree with Mark. It's simple hypothesis testing. "Is subset A significantly different from the total population?" (I think I saw your question the other day about ZCTA, which the same thing applies to.) However, if your subset comprises a very large portion of the population, you might get non-intuitive results. For example, comparing males to the total population. Since the only other option is female, so you may want to divide into two independent samples of male and female. Although there might be statistical vagaries, as a practitioner I would compare two geographic samples that are not independent, so long as the "population" sample is much larger.

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