- The purpose of this project is to analyze district-wide standardized test results.
The purpose of this project is to analyze district-wide standardized test results. Data is aggregated to show trends in school performance. Analysis was performed using School and Student Data. The school board will be using these results to make strategic decisions regarding future school budgets and priorities.
This project uses the Pandas library to manipulate data into tables that allow for aggregating and summarizing of district and school data. Array calculations are performed to create a snapshot of school district's key metrics. Analysis done to show trends such as top peforming schools, bottom performing schools, math and reading scores by grade, and scores by school spending, size, and school type.
- As a whole, schools with higher budgets, did not yield better test results. By contrast, schools with higher spending per student actually ($645-675) underperformed compared to schools with smaller budgets (<$585 per student).
- As a whole, smaller and medium sized schools dramatically out-performed large sized schools on passing math performances (89-91% passing vs 77%).
- Math passing rates are always consistently lower across every metric, but the difference between math and reading passing rates is greater among lower performing schools, large schools, and higher spending per student which all seem to correlate.
- Average math and reading scores stay consistent across grade level when grouped by school.
- In general (one exception), per student spending is higher in bottom performing schools than top performing.
- The same phenomenon is seen with high and low per student spending brackets and district versus charter schools.
- However, more analysis will be required to extract from various sources if the effect is due to school practices or the fact that charter schools tend to serve smaller student populations per school.