Advanced A/B Testing Statistical Framework

Create a robust Python framework for conducting statistical A/B tests with advanced features including multiple hypothesis testing correction, effect size calculation, and comprehensive reporting. Utilize scipy.stats for statistical computations, implement bootstrapping techniques, generate interactive visualizations with plotly, and develop a flexible configuration system that allows customizable significance levels and test methodologies. The solution should automatically handle sample size determination and provide clear, actionable insights for decision-makers.