Students Performance Analysis

Overview

The "student-performance.ipynb" notebook explores student performance data through exploratory data analysis (EDA), statistical analysis, and visualization techniques. The dataset used "Students_Performance_Data.numbers" contains 1000 test scores (Math/ Reading/ Writing) from (female/male) students of different races/ethnicities.

Contents

The notebook is divided into 5 parts, each answering a different question:

1- Are there subjects where a gender is better than the other?

2- Is there a relationship between race/ethnicity and test score ?

3- How effective the test preparation course is ?

4- Does the level of education of parents impact their children's performance ?

5- At what extent can the lunch taken before a test affect the student performance ?

Usage

To run the notebook locally:

1. Clone the repository:

   git clone https://github.com/patime07/Students_Performance_Analysis.git
   

2. Navigate to the project directory:

   cd Students_Performance_Analysis
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

   (Ensure you have Python and Jupyter Notebook installed.)

4. Start Jupyter Notebook:

   jupyter notebook
   

5. Open student-performance.ipynb in the browser and run each cell sequentially to replicate the analysis.

Requirements

• Python 3.x
• Jupyter Notebook
• Pandas, NumPy, Matplotlib, Seaborn (install via requirements.txt)

License

This project is licensed under the Apache License 2.0