The scatterplot above represents the correlation of two different income populations and their respective
relationships with the percentage of the populations which have been told they suffer from depression. The
first income population (%Single and Rich) shows the percentage of people, by state, who are single and made
more $200,000 in the last 12 months. The second income population (%Poor with Family) represents the percentage of
the popluation, by state, who had families and made less than $10,000 in the the 12 last months. Both datasets are
are plotted against the y axis which represents the percentage of state populations that have been told they were
depressed. According the data analysis, there doesn't seem to be any definitive correlation to between either
income poplulations and the percentage of people who had been told they were depressed. The first income population
(%Single and Rich) had a correlation coefficient of (-.36668) and the second income population (%Poor with Family)
had a correlation coefficient of (.0215). Neither coefficients are sufficient to support a determination based solely
on these factors. It is important to note that the correlation of (%Single and Rich) is 17 times greater than the
correlation of (%Poor with Family). Also, the negative correlation of the (%Single and Rich) population indicates
that the percentage of people who have been told that they were depressed decreases as the percentage of the population
that is single and rich increases. Conversely, the (%Poor with Family) population has a positive correlation albeit
negligible at (.0215). Also, Puerto Rico had the greatest percentage of families (13.3%) making less than $10,000 with
the percentage depressed at (18.5%), and the District of Columbia had the greatest percentage (8.4%) of single households
making more than $200,000 with percentage depressed at (18.1%). Based on our findings in this analysis is indeterminate
as to whether or not income levels are related to depression amongst the populations. Of course, there are innumerable
other socieconomic factors that could affect the percentage of the population that has been told they have forms of
depression. This is simply a preliminary analysis to find the correlations, if any, of these two particular factors.