Background:
"Maria has gotten a new version of the student data with several changes. This includes an additional column: "school budget". She wants you to rework part of your analysis by using the new dataset.
In this module, you'll be assisting Maria, the chief data scientist for a city school district. Maria is responsible for analyzing information from a variety of sources and in a variety of formats. In this role, she is tasked with preparing all standardized test data for analysis, reporting, and presentation to provide insights about performance trends and patterns.
These insights are used to inform discussions and strategic decisions at the school and district level. In this module, you'll be helping Maria analyze data on student funding and students' standardized test scores. You'll be given access to every student's math and reading scores, as well as various information on the schools they attend. Your task is to aggregate the data and showcase trends in school performance."
In this assignment, we have been tasked to join a team of data analysts with a specific toolkit called the PANDAS library. It's a toolkit to make data analysis like a breeze. PANDAS provides lots of tools to make tables of information that will be easier to show your non-technical coworkers. My first discovery was related to missing, duplicated, or mistyped values. These could easily skew your data accidently if you didn't realize that they were there or not. The average reading score was within 1% of each other. On the other hand, there was less than a 5% difference between charter and public schools for math scores. You must not forget that we dropped almost 2000 reading scores, 1000 math scores, and 2000 duplicate values. This leads me to say it was inconclusive to say whether sending your child to charter school would lead to better test scores. Another analysis that I would find beneficial, would be to see the average reading score by school type. School budgets by school and grade for each test score would be insightful. It may highlight some teaching deficiencies.
One ought to remember that school type is but one factor for a child's success. The data file provided for this analysis is a good starting point, but lacks other factors such as teacher rating and parent’s socioeconomic status. It is fairly common knowledge that students that do not get the proper sustenance makes learning more difficult.
American Psychological Association. (2017, July). Education and socioeconomic status factsheet. American Psychological Association. Retrieved December 9, 2022, from https://www.apa.org/pi/ses/resources/publications/education