Aim of this analysis is to see the trends of standardized test scores among different schools in a specific district. This project will help the authorities to understand the reasons behind the successes/failures of different schools and act accordingly in the future.
There are two data sets, which are 'schools data' and 'students data'. Before starting analysis, these two datasets were merged.
This school district has 15 schools (7 district public, 8 charter) and 39,170 students who are attending to these schools. The school district has total budget of $24,649,428.
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District summary table shows that average reading test scores are higher than average math scores.
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There is negative relationship between test scores and school budgets. This area needs further investigation about the reason behind this trend. This analysis shows us that more money is not the basic motive behind the success.
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There is negative relationship between test scores and school size. From this finding, we can infer that there is an improvement opportunity for school district by thinking about investments on new school constructions which will help to decrease the number of students per school.
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Charter Schools have higher average test scores than distict-public schools in all metrics. When we sort the school summary table according to total number of students, we can see that charter schools are the schools with least number of students. Therefore, charter schools success will come from their size.
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Stating data with visual tools, like graphs, will help us to understand the trends more easily. Moreover, before reaching to conclusion about trends, it will be a good idea to look at the statistical significances of the differences between test scores in terms of many different metrics.
Dataframe includes:
- Total schools
- Total students
- Total budget
- Average math score
- Average reading score
- % passing math (the percentage of students who passed math)
- % passing reading (the percentage of students who passed reading)
- % overall passing (the percentage of students who passed math AND reading)
Data Frame includes below key metrics about each school:
- School name
- School type
- Total students
- Total school budget
- Per student budget
- Average math score
- Average reading score
- % passing math (the percentage of students who passed math)
- % passing reading (the percentage of students who passed reading)
- % overall passing (the percentage of students who passed math AND reading)
DataFrame highlights the top-5 performing schools based on % Overall Passing. Includes the following metrics:
- School name
- School type
- Total students
- Total school budget
- Per student budget
- Average math score
- Average reading score
- % passing math (the percentage of students who passed math)
- % passing reading (the percentage of students who passed reading)
- % overall passing (the percentage of students who passed math AND reading)
DataFrame highlights the bottom-5 performing schools based on % Overall Passing. Includes the following metrics:
- School name
- School type
- Total students
- Total school budget
- Per student budget
- Average math score
- Average reading score
- % passing math (the percentage of students who passed math)
- % passing reading (the percentage of students who passed reading)
- % overall passing (the percentage of students who passed math AND reading)
This dataframe lists the average math score for students of each grade level (9th, 10th, 11th, 12th) at each school.
This dataframe lists the average reading score for students of each grade level (9th, 10th, 11th, 12th) at each school.
This dataframe breaks down school performance based on average spending ranges (per student) and includes the following metrics:
- Average math score
- Average reading score
- % passing math (the percentage of students who passed math)
- % passing reading (the percentage of students who passed reading)
- % overall passing (the percentage of students who passed math AND reading)
This table breaks down school performance based on school size (small, medium, or large).
This table breaks down school performance based on school type (district public or charter)
