Unveiling Unseen Insights: Quality Management and Business Optimization Through the Analysis of Product Sales Patterns With Categorical and Continuous Predictors in a Unique Dataset

This investigation explores e-commerce product sales patterns, integrating Quality Management and Business Optimization perspectives.We analyze product listings, ratings, and sales metrics using a unique dataset from data.world.com,sourced from Wish.com.Our predictive model unveils correlations among categorical and continuous predictors, spotlighting their role in predicting unit sales.Employing robust linear regression, we assess predictor significance via t-tests, hypothesis evaluations, and ANOVA.Model selection, guided by AIC, identifies the optimal fit.Outliers, influential points, and assumptions are evaluated.Employing data visualization, we present results comprehensively.This study empowers stakeholders with insights into e-commerce dynamics, Quality Management, and Business Optimization for informed decision-making.