Student Performance EDA

Necessary Libraries

• Pandas
• Numpy
• Matplotlib
• Seaborn

Problem Statement:

• gender : Gender of the student
• race/ethnicity : Race of the Student As Group A/B/C
• parental level of education : What is the education Qualification of Students Parent
• lunch : Whether the lunch is Standard type/Free lunch or Some discounted lunch
• test preparation course : Whether Student has Taken or not and Completed
• math score : Scores in Maths
• reading score : Scores in Reading
• writing score : Scores in Writing

Objective of this Analysis:

• To understand the how the student's performance (test scores) is affected by the other variables (Gender, Ethnicity, Parental level of education, Lunch, Test preparation course).

Exploratory Data Analysis includes:

• Analysis insights in the dataset.
• To understand the connection between the variables and to uncover the underlying structure
• To extract the important Variables.
• To test the underlying assumptions.
• Insights with Suitable Graphs and Visualizations.
• Inferences with supporting Analysis and Visualizations.