Where's the Money?
I concentrated my next part of calculations on income. Although I believed that low income might be a sufficient indicator of AIDS, the correlation was no where near significant. For instance, below I portray the two lowest income ranges, which is income less than $10,000 have a correlation of +0.0938 and income from $10,000 to $14,999 have a correlation of +0.0041. Therefore, no conclusions could be made with low income. After the low income calculations, I estimated that high income might have a relation with a high income indicator. Again, I found no correlation between the highest two income ranges and the AIDS rate, but I did find a correlation between the third highest income ranges. $125,000 to $149,999 had a correlation of -0.3408, which is between p-value=.10 and p-value=.05. Therefore it shows about a 93% confidence level that a negative (indirect) relationship does exist. This was actually the only correlation I could find with income. Also, I did find that the population above the poverty line posses a correlation -0.3232, which again leaves a p-value from 0.1 to 0.05. The poverty line is about $13,000. Therefore we can conclude with about a 93% confidence level that if the population above the poverty line increases than the AIDS rate will decrease. An explanation of this occurrence may be if people can afford treatment or drugs for AIDS, they will not die of the disease. Also, Otisville has the lowest population above poverty level, this shows that individuals don’t make a lot in jail.
