the "impact" quantity
1
looking at the bottom plot ... which data set is more 'important' – the Rep states or the Dem states?
the slope of the Rep states best-fit line is larger, does that make Rep states data more significant?
the correlation value of the Rep states best-fit line is larger, does that make Rep states data more significant?

2
The correlation values of +1, 0, –1 are well-defined; but the in-between values are not well-defined: I have learned that when using r-values to give meaning to data, that r-values need to be compared "relatively". Still, I am not sure how much more meaningful is data with an r-value of 0.62 compared to data with an r-value of 0.50. It would seem that 0.62 is more meaningful than 0.50.

3
There is associated with r-values a P-value
– The r-value is a measure of the "strength" of the data used to fit the slope of the best-fit line.
– The P-value is the probability of the r-values non-randomness: a low P-value indicates that the given r-value is less likely to be due to random fluctuations; a large P-value indicates the data is more likely to be due to random fluctuations of the Population; thus, a low P-value has more significance than a large P-value.
– defining the "impact" as "r-value/P-value" yields a quantity which can be used to quantify the significance of the data points about a best-fit line.

4
For the B/W income ratio vs B/W incarceration ratio plot, the Rep best-fit line has an 'impact' of "–306" and the Dem best-fit line has an 'impact' of "–1.3".
Conclusion: The Rep states' data is more significant/important than the Dem states' data.