A data-driven A/B testing project comparing website performance under Light and Dark themes. Analyzes user engagement metrics using statistical tests, correlation analysis, and predictive modeling to identify behavioral patterns and theme effectiveness. Built in Python using Jupyter Notebook with pandas, seaborn, and scikit-learn.
python numpy scikit-learn pandas data-visualization scipy ab-testing behavior-analysis jupyter-notebooks hypothesis-testing conversion-rate website-performance correlation-analysis click-through-rate welch-t-test matploitlib bounce-rate
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Updated
May 9, 2025 - Jupyter Notebook