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Pridemore and Freilich analyzed homicide victimization rates by state for white non-hispanics. Here is the summarization of the regression model. 

variable          Intercept RD    PS    YOUNG  DIV     UN    SOUTH
beta               -5.230   0.109 1.758 18.293 5.710   5.710 0.257
stand.coef.                0.302 0.216  0.293 0.524   0.118 0.260
p.value            0.001    0.021 0.014 <0.001 <0.001  0.129 0.010

Where, RD is a measure of deprivation, PS is a measure of population structure, DIV is a divorce rate, UN is unemployment rate, SOUTH is a dummy variable that is 1 for a collection of 16 southern states.

The author tells from the summarization, "White non-hispanic rates remained significantly higher in the south when controlling for the covariates."

Now, the question is,
- How the authors reached this conclusion from this regression.
- Do I need to check any assumptions before accepting this conclusion as valid? If so, then what are those assumptions?

I appreciate if I would get a full explanation from this question.

Salah Uddin
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  • The coefficient of `SOUTH` is positive with a small p-value. Yes, you need to check assumptions: please see https://stats.stackexchange.com/search?q=regression+assumption. – whuber Apr 06 '19 at 16:49
  • I do not get it easy to relate this quesion with the other questions. I appreciate, if I would get specific answer from this question. – Salah Uddin Apr 06 '19 at 17:12
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    If you would like a specific answer, then you need to make the question more specific. As it stands, you are asking the same thing asked in the duplicate: namely, what are the assumptions underlying this analysis. – whuber Apr 06 '19 at 17:20
  • You are asking how to interpret the results which is understandable. But on the other hand there are thousands of study results which would make it inefficient to clarify how to interpret each of them so you should rather ask a specific statistical question. There will definitely be ressources explaining how to interpret OLS outputs and what assumptions there are what makes it a duplicate. –  Apr 07 '19 at 00:35

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