Comprehensive portfolio demonstrating a variety of real-world statistical analysis projects using Python and Jupyter Notebooks. Each project folder presents a unique data scenario, complete with code, methodology, and business insights.
- Credit-Risk-Analysis
Analyze lending and credit risk, build models to predict defaults, and evaluate model performance using data science techniques. - ab-testing-analysis
Design, execute, and interpret A/B tests to measure business improvements, including methodology documentation and Python code. - customer survey data analysis
Survey design quality, missing data handling, experiment results, and customer segmentation. In-depth insights from retail survey data. - sales_performance_analysis
Sales data analysis with intermediate-level statistical tests and visualization. Methods used to optimize sales strategies. - sales_performance_analysis(Intermediate)
Further exploration of sales performance with deeper statistical modeling and advanced sample analysis.
git clone https://github.com/Hamdaan-P/Statistical-Analysis-Portfolio.git
cd <project-folder>
# Open Jupyter Notebook or Power BI files as required- Python (pandas, numpy, scipy, matplotlib, seaborn)
- Jupyter Notebook
This repository showcases skills in statistical analysis, data visualization and Python programming. Each project folder contains:
- Example datasets
- Notebooks, dashboards, and code
- Project-readmes describing approach, findings, and business impact
Visit each project folder for project-specific documentation and code.
This project is licensed under the MIT License.
Feel free to update or add more details for each project as your portfolio grows!