Stats-CI 0.1.2

# Confidence Interval Library

The Confidence Interval Library is a Python package for calculating confidence intervals for various statistical metrics. This library simplifies the process of estimating the confidence intervals around a sample mean, proportion, or other statistical estimates.

## Installation

You can install the Confidence Interval Library directly from PyPI:

```bash
pip install confidence_interval

Features

• Mean Confidence Interval: Calculate the confidence interval for the mean of a dataset.
• Proportion Confidence Interval: (If applicable) Calculate the confidence interval for the proportion of a dataset.
• Custom Confidence Levels: Allows specifying different confidence levels.

Usage

Here is how you can use the Confidence Interval Library:

Calculating Mean Confidence Interval

from confidence_interval import mean_confidence_interval
data = [1, 2, 3, 4, 5]
mean, lower_bound, upper_bound = mean_confidence_interval(data)
print("Mean:", mean)
print("Lower bound:", lower_bound)
print("Upper bound:", upper_bound)

Requirements

• Python 3.6+
• NumPy
• SciPy

Contributing

Contributions are welcome! Please fork the repository and open a pull request with your additions, or open an issue if you find any bugs or have suggestions.

License

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

Authors

• Subashanan Nair - Initial work - SubaashNair

Acknowledgments

• To my students
• Logic and Mathematics
• Life