SaurabhSSB/statistics_workout

A collection of Python scripts demonstrating core statistical concepts like percentile analysis, Z-scores, modified Z-tests, and cosine similarity with real datasets and visualizations.

23
/ 100
Experimental

This project helps data analysts and researchers understand their datasets better by demonstrating core statistical concepts. It takes raw data, such as household sizes, BMI records, or income figures, and applies methods like percentile analysis and Z-scores to identify outliers and understand distributions. The output includes visualized data and calculated metrics to help make data-driven decisions.

No commits in the last 6 months.

Use this if you need to learn or apply fundamental statistical techniques like outlier detection, percentile analysis, or similarity measurements to real-world data and see the results visually.

Not ideal if you're looking for a plug-and-play application for advanced machine learning models or real-time data processing.

data-analysis statistical-modeling outlier-detection data-cleaning data-visualization
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

How are scores calculated?

Stars

13

Forks

Language

Python

License

MIT

Last pushed

Jul 12, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/SaurabhSSB/statistics_workout"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.