The pie chart below shows a distribution of students from different Ethnicity/Race within the District. As you can see, the district is made up of mainly two Ethnicity - White and African Americans, each taking from 36% and 37% respectively. While Hispanic, Asian Americans and Native Americans taking up less than 30% of the population.
A further breakdown of the data is shown in the bar chart below. There are 12,847 number of African American students, while the number of white students coming close at 12,391. The two population being the main groups should represent some pattern within the district, right?
The pie chart below shows the ratio of schools labeled high poverty within the district, showing 43.84% of schools belonging to high poverty category. How might this relate to the race distribution we’ve discussed?
When the race distribution data is combined with the distribution of poverty/non-poverty school, a conclusion can be drawn - African Americans students in the district takes up the majority percentage in high poverty schools, while white students takes up the majority percentage in non poverty schools. Might there be a correlation between the two data entity (Race and Poverty)?
Another representation is crafted to illustrate the relationship. It shows how African American students have roughly the same number in both high poverty and non poverty schools, while the white student group having the biggest difference in numbers in two different school types. Showing a disproportionally more white students in the non poverty schools.
Lets now focus on the subsets of the two data entities for a closer analysis. Two histograms are shown below, showing the distribution of the students from the two main races in high poverty and non poverty schools. The patterns in both graphs supports the observation made from previous graphs:
Lastly to solidify findings, we can see that the regression line between % of Reduced price lunch and % of White American Students displays a negative correlation, with analytics showing the relationship being - 0.96 and P value above 6. Suggesting schools with more white Americans generally requires less reduced price lunches.
Conclusion
The pattern shown in this report represents a existing problem that has been long coming - the inequality in quality of life between races in America. It is hard to pin point the exact cause of such issue, it can be societal, historical or cultural. More data is needed to come up with a more rounded solution to this problem. For now, more resources should be dedicated to help students in need, such that students in high poverty areas can acquire education at an affordable rate.