Metadata-Version: 2.1
Name: correlation-stats-analyzer
Version: 0.1.1
Summary: A simple tool to compute and interpret Pearson correlation coefficients.
Author: Md. Ismiel Hossen Abir
Author-email: ismielabir1971@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: License

# correlation_stats_analyzer

A lightweight Python package to compute and interpret the strength and direction of correlation between two numerical datasets using the Pearson Correlation Coefficient.

---

## Features

- Compute the Pearson correlation coefficient between two numeric lists.
- Interpret the result in terms of strength and direction (e.g., "Strong Positive").
- Zero dependencies â€“ works with standard Python only.
- Designed for data science beginners, educators, and small-scale analysis scripts.

---

## Installation

```bash
pip install correlation_stats_analyzer
```

## Usage Example

```bash
import correlation_stats_analyzer as csa

x = [10, 20, 30, 40, 50]
y = [12, 22, 29, 41, 52]

r = csa.correlation_r(x, y)

strength, direction = csa.interpret_r(r)

print(f"Pearson r: {r:.4f}")
print(f"Strength: {strength}, Direction: {direction}")
```
