The following dataset tells us about the 1000 students whose marks in Maths, Reading and Writing have been provided. Our aim is to provide the following results using Exploratory Data Analysis(EDA) using NumPy, Pandas, Matplotlib and Seaborn. This is the first milestone in this project. In the future, Linear Regression Algorithm will be added to the dataset to make a model denoting the aspects of getting marks and being allured by other factors in life.
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).
What to do in Exploratory Data Analysis: To Analyse 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. Provide Insights with Suitable Graphs and Visualizations. Write all your inferences with supporting Analysis and Visualizations.