Exploratory Data & Statistical Analysis | Challenge Q & A

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