SchoolPerformanceAnalysis

Summary

The SchoolPerformanceAnalysis project aims to analyze school performance based on various metrics. The analysis consists of three major parts: Data Collection and Preparation, Data Analysis, and Conclusion and Comparisons. By examining factors such as school spending, school size, and school type, the project seeks to gain insights into the relationships between these factors and student performance.

Introduction

This analysis consists of three major parts:

• Data Collection and Preparation
• Data Analysis
• Conclusion and Comparisons

Data Collection and Preparation

The primary data for this task includes various metrics of schools within a local government jurisdiction such as the total number of schools, total students, total budget, average scores in math and reading, and percentage of students passing in math, reading, and both. The data was collected, cleaned, and prepared for the subsequent analysis. The validity of the conclusions is based on the assumption that the averages derived from the data are accurate.

Data Analysis

School Spending

The analysis phase of the task involved exploring correlations between school spending and student performance. The results indicated a weak yet statistically significant negative relationship between per-student budget and average scores in math and reading. However, this relationship may not hold universally true, and likely other factors could influence student performance.

School Sizes

The task also involved the comparison of school sizes with the overall passing rate. According to the analysis, smaller schools tend to yield higher overall passing rates. However, this is a generalized trend and it may vary on a case-to-case basis depending upon various factors like quality of education, available resources, and demographics of the student body.

School Type

The final part of the data analysis involved comparing average scores and passing percentages between government and independent schools. The results indicated that independent schools generally outperformed government schools in these metrics.

Conclusion and Comparisons

While the analysis does hint at correlations between spending, size, type of schools, and student performance, it is essential to consider that these observations may not be universally applicable. Further, more comprehensive research is needed to gain a fuller understanding of these relationships. It is also crucial to include additional influential factors such as socio-economic status and school funding in the analysis to enhance the accuracy of the conclusions.

Tools

• Python
• Pandas
• Jupyter Notebook

Files

• Data Analysis Script
• Complete list of Schools
• Complete list of Students