Student Study Performance Analysis https://www.kaggle.com/datasets/impapan/student-performance-data-set
This project explores the factors affecting student performance based on the Student Study Performance Dataset. The analysis aims to investigate the following questions:
Who performs better: Males or Females?
What other factors (e.g., ethnicity, lunch type) influence student marks?
The project involves data cleaning, data visualization, and statistical hypothesis testing (Z-test and Q-test) to draw insights from the dataset.
Project Overview
The dataset contains information about students' demographic attributes, study time, and their performance on various assessments. By analyzing this data, we attempt to uncover patterns and answer questions about how various factors like gender, ethnicity, and lunch type impact students' academic performance.
Key Steps in the Analysis Data Cleaning
Handling missing values
Correcting any inconsistencies in the dataset
Formatting columns for analysis
Data Exploration
Descriptive statistics (mean, median, standard deviation)
Visualizations (histograms, bar charts, scatter plots)
Statistical Testing
Z-Test: Comparing the means of two groups (e.g., male vs. female students) to see if there's a significant difference in performance.
Q-Test: Identifying any outliers in the dataset that could skew results.
Hypothesis Testing
Testing the impact of factors like ethnicity and lunch type on student performance. Results and Insights
Conclusions on gender differences in performance
Insights into how other factors like ethnicity and lunch type influence student marks
Technologies Used Python
Pandas for data manipulation
Matplotlib and Seaborn for data visualization
Scipy for statistical testing
Jupyter Notebook for documentation and analysis
Dataset
The dataset used in this analysis is the Student Study Performance Dataset. It contains the following features:
Gender: Male or Female
Ethnicity: Ethnic background of the student
Lunch: Type of lunch (e.g., standard or free/reduced)
Study time: Amount of study time per week
Marks: Final grades of the student
This project was created by me and @jouditafran.