Learn Statistics by building 10 hands-on, visual, and interactive projects inspired by key topics in foundational probability and statistics.
This repository is my personal project to Learn Statistics by building real, practical projects aligned with core statistical ideas like probability, distributions, sampling, hypothesis testing, and more.
- Build strong statistical intuition through simulation and visualization
- Learn practical statistics concepts by implementing them from scratch
- Make abstract concepts tangible: sampling distributions, p-values, the Central Limit Theorem, and more
- Lay a solid foundation for data science and machine learning
| No. | Core Project | Focus Area | Outcome / Learning Goal |
|---|---|---|---|
| 1 | Descriptive Stats Analyzer | Summary Statistics | Compute and interpret central tendency and spread from real data |
| 2 | Data Visualization Dashboard | Visualizing Distributions | Create compelling visual summaries using plots and correlation maps |
| 3 | Probability Simulator | Basic Probability & Simulation | Simulate randomness and visualize probabilities |
| 4 | Distribution Explorer | Distributions (Binomial, Normal, etc.) | Model, compare, and interpret theoretical vs real-world distributions |
| 5 | Sampling & CLT Demo | Sampling & Central Limit Theorem | Understand random sampling and visualize the CLT |
| 6 | Hypothesis Testing Engine | Confidence Intervals & Hypothesis Testing Basics | Conduct tests on population claims and estimate error |
| 7 | t-tests & ANOVA Toolkit | Group Comparison Tests | Perform t-tests and ANOVA to compare groups |
| 8 | Simple Linear Regression Explorer | Basic Predictive Modeling | Fit and evaluate a single-feature linear model |
| 9 | Multiple Regression Studio | Multivariable Modeling | Work with multiple predictors and address assumptions |
| 10 | Categorical Data & Capstone Project | Categorical Analysis & ML Context | Apply stats to real classification problems and summarize full stack |
I use and recommend starting with these:
- Python 3.10+
- Jupyter Notebook / JupyterLab
- NumPy
- Pandas
- Matplotlib
- Seaborn
This is my personal learning journey, but I welcome feedback, suggestions, and pull requests! If you create your own variation or improve a project, feel free to contribute.
This project is licensed under the MIT License. See LICENSE for details.
Created and Maintained by RM Villa