StatAnalyzer Pro is a web-based statistical analysis tool that allows users to upload datasets and perform various statistical analyses, including hypothesis testing, regression modeling, visualization, and more. Built with Django and Python, it provides an intuitive interface for data exploration and statistical analysis.

• Data Upload: Supports CSV, Excel (XLSX), and JSON formats
• Data Summary: Automatic variable type detection and descriptive statistics
• Hypothesis Testing:
  • Independent T-Test
  • One-Way ANOVA
  • Chi-Square Test
  • Mann-Whitney U Test
• Regression Analysis:
  • Linear Regression with VIF diagnostics
  • Logistic Regression with performance metrics
• Visualizations:
  • Histograms
  • Box Plots
  • Scatter Plots
  • Correlation Matrices
• ANCOVA: Analysis of Covariance
• AI Insights: Automated interpretation of results
• Report Generation: Download PDF reports of your analyses

• Python 3.8+
• pip
• virtualenv (recommended)

1. Clone the repository:

   git clone https://github.com/fkaan/Statistics-Calculator.git
   cd stat-analyzer

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Linux/macOS
   # On Windows:
   # venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Apply migrations:

   python manage.py migrate

5. Create a superuser (optional):

   python manage.py createsuperuser

6. Run the development server:

   python manage.py runserver

7. Open in your browser:

   http://localhost:8000
   

• Navigate to the home page
• Upload your dataset file or paste CSV data
• Click "Analyze Now"

• View variable types and descriptive statistics
• Examine data preview

• Use the tabs to navigate between different analysis types
• Select variables and parameters for each test
• Click "Run Analysis" to see results

• After any analysis, click "Download Report" to get a PDF
• Use "Generate AI Insights" for automated interpretation

• Click "Upload New Data" to analyze a different dataset

• Backend: Django (Python)
• Frontend: Bootstrap 4, jQuery
• Data Analysis: Pandas, NumPy, SciPy, Statsmodels, scikit-learn
• Visualization: Plotly
• PDF Generation: ReportLab
• AI Integration: OpenAI API (optional)

stat-analyzer/
├── analyzer/               # Main Django app
│   ├── migrations/         # Database migrations
│   ├── static/             # Static files (CSS, JS, images)
│   ├── templates/          # HTML templates
│   ├── utils/              # Utility functions
│   ├── admin.py            # Admin configuration
│   ├── apps.py             # App configuration
│   ├── forms.py            # Form definitions
│   ├── models.py           # Database models
│   ├── urls.py             # URL routing
│   └── views.py            # View functions
├── stat_analyzer/          # Project configuration
│   ├── settings.py         # Django settings
│   ├── urls.py             # Main URL routing
│   └── wsgi.py             # WSGI configuration
├── requirements.txt        # Python dependencies
└── manage.py               # Django management script

Create a .env file in your project root with the following variables (if needed):

DEBUG=True
SECRET_KEY=your-secret-key-here
OPENAI_API_KEY=your-api-key-if-using-ai  # Optional

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a new branch:

   git checkout -b feature-branch

3. Make your changes and commit:

   git commit -am 'Add new feature'

4. Push to the branch:

   git push origin feature-branch

5. Create a new Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.

• Add time series analysis capabilities
• Implement user accounts to save analysis history
• Add more visualization options
• Support for larger datasets with pagination
• Dockerize the application for easier deployment

[![Python Version](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/)
[![Django Version](https://img.shields.io/badge/django-3.2+-green.svg)](https://www.djangoproject.com/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

You can add these right under the title as already shown.

Built with ❤️ for data scientists, researchers, and students.