The purpose of this repository is mainly to showcase python and pandas skills involving merging, grouping, cleaning, etc that are required for working with data
This repository provides a multidimensitonal analysis on how poverty affects test scores alongside other variables.
Questions include:
-How does poverty affect academic performance for elementary, middle and high schoolers?
-Are different academic subjects affected differently by poverty?
-How do math and reading scores change as a child develops, when aslo taking poverty into account?
-What role do Charter Schools play in student achievement when taking into account poverty?
All of the code, variable meanings, results and interpretations will be included in the Jupyter notebook attatched to the repository
Main Findings(more in depth analysis can be found within code explinations)
-Poverty has a large negative effect on test scores
-As children develop, math scores get progressively worse while writing scores get progressively better
-Math scores are more affected by poverty relative to reading scores
-Charter schools in the similar economic circumstances as non-charter schools do not have significantly better test scores
All of the data used can be found from two datasets created by the California Assessment of Student Performance and Progress(CAASPP) which are listed below.
My data on percentage of students eligble for free lunch(my rough poverty estimate) can be found by following the link below and downloading the "Unduplicated Student Poverty – Free or Reduced-Price Meals Data 2023–24" excel file https://www.cde.ca.gov/ds/ad/filessp.asp
My data on test scores can be found by clicking the link below and downloading the csv file for "2023–24 California Statewide research file, All Students, fixed width" https://caaspp-elpac.ets.org/caaspp/ResearchFileListSB?ps=true&lstTestYear=2024&lstTestType=B&lstCounty=00&lstDistrict=00000