

A fast, practical session to learn how to explore datasets, uncover patterns, and validate insights with core statistics—using Python in Google Colab. **What you’ll learn** * Clean and profile data (missing values, outliers, distributions) * Visual EDA (histograms, box/violin plots, pairplots) to spot signals * Essential stats for decisions: confidence intervals, A/B testing basics, correlation vs. causation * Quick reporting: turning EDA findings into clear recommendations **Format & requirements** * Live demo + guided mini-exercise (bring a laptop; Google Colab link provided) * Audience: beginners to intermediate (no heavy math required) * Tools: Python, pandas, matplotlib, scipy * Takeaway: a reusable EDA notebook template and checklist
