Perform comprehensive multi-dimensional statistical correlation analysis on **quarterly sales data across 15 product categories, customer demographics, marketing spend, and seasonal factors over 5-year period** by executing advanced Pearson, Spearman, and Kendall correlation matrices with significance testing, conduct **time-series trend analysis with ARIMA(2,1,2) modeling and seasonal decomposition identifying monthly/quarterly patterns** using polynomial regression, seasonal decomposition, and ARIMA forecasting models, identify **customer segment clustering patterns, sales velocity outliers, and promotional impact anomalies** through clustering algorithms, outlier detection using Z-score and IQR methods, and statistical anomaly identification, generate **revenue forecasting framework with 95% confidence intervals, hypothesis testing for marketing ROI effectiveness, and customer lifetime value predictions** with confidence intervals, hypothesis testing results, R-squared values, p-values under 0.05 significance threshold, correlation heatmaps with coefficient strengths, trend visualization with 95% prediction bands