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A Python package for descriptive and advanced statistical analysis

Project description

Got it 👍 You’re building a Python package called aistats (AI + Statistics). Here’s a clean, professional README.md draft you can directly use in your project.


# aistats

**aistats** is a Python package that bridges the gap between **Artificial Intelligence (AI)** and **Statistics**, providing tools that range from **basic descriptive statistics** to **advanced machine learning and AI-driven statistical analysis**.  

It is designed for students, researchers, and professionals who want a single package to handle everything from **basic stats** to **AI-powered insights**.

---

## ✨ Features

- 📊 **Descriptive Statistics**  
  - Mean, Median, Mode, Variance, Standard Deviation, Skewness, Kurtosis  

- 📈 **Inferential Statistics**  
  - Hypothesis Testing (t-test, chi-square, ANOVA, etc.)  
  - Confidence Intervals  
  - Correlation & Regression  

- 🧠 **AI + Machine Learning**  
  - Linear & Logistic Regression  
  - Decision Trees, Random Forest  
  - Neural Network-based estimations  
  - Information Equivalent Design for Regression Models  

- 📚 **Educational Support**  
  - Step-by-step explanations of results  
  - Examples from real-life domains (Agriculture, Education, Sports, Engineering, etc.)  

---

## 📦 Installation

You can install the package (once uploaded to PyPI) using:

pip install aistats

```
aistats/
│── __init__.py
│── descriptive.py      # Basic statistics
│── inferential.py      # Hypothesis testing, probability
│── ml.py               # AI + Machine Learning models
│── design.py           # Information Equivalent Design algorithms
│── utils.py            # Helper functions
```
## 🤝 Contribution

Contributions are welcome! Please fork the repo and submit a pull request.

---

## 📜 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

---

## 🙌 Acknowledgments

This package is inspired by the need to **combine traditional statistical methods with modern AI approaches** to make statistical analysis smarter, faster, and more interpretable.

```
## 👨‍💻 Author

**Name:** Rohit Kumar Behera  
**Profession:** Mathematics Teacher, Researcher in Statistics & AI  
**Location:** Odisha, India  

- 📧 Email: rohitsmartbehera@gmail.com  
- 🌐 GitHub: [github.com/muinrohit]
- 📝 Research Interests: Statistics, Machine Learning, AI Applications in Real-life Problems  
- 📊 Projects: `aistats`, and educational tools for applied statistics  

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