Saturday, July 24, 2021

Public School Staffing by State - Exploratory Data Analysis (EDA) by David White

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Exploratory Data Analysis

Public school data by state (part 2 of 2)

David White | Saturday, July 24, 2021

What is Exploratory Data Analysis?

Exploratory data analysis (EDA) is a technique used by data scientists to inspect, characterize and briefly summarize the contents of a dataset. EDA is often the first step when encountering a new or unfamiliar dataset. EDA helps the data scientist become acquainted with a dataset and test some basic assumptions about the data. By the end of the EDA process, some initial insights can be drawn from the dataset and a framework for further analysis or modeling is established.

This exploratory data analysis explores a dataset containing information on public schools in the United States. The underlying data was published by the United States Department of Education.

See also: Exploratory Data Analysis: Public School Demographics

Here are the takeaways from the dataset:

• The dataset contains one row for each US state plus the District of Columbia

• The dataset contains totals by state of the number of public schools in operation, total numbers of students and total for school teachers and administrators. The total number of students are roughly proportionate to the other three metrics.

• In terms of school staffing, generally speaking, the total number of students is roughly proportionate to the other three metrics

Next Steps:

Possible avenues for further research and analysis:

• There were some outliers shown in each scatterplot. It would be worth investigating why those particular states differ from the norm

• This data could be joined with metrics on student achievement to study the correlation, if any, between staffing and student achievement

• This data could be joined with metrics on income levels to study the correlation, if any, between income and student achievement