The document discusses exploratory data analysis techniques used to analyze a telecommunications customer churn dataset containing 3,333 records and 20 variables. Key techniques included: 1. Examining relationships between categorical variables like international plan and voice mail plan to churn, finding customers in international plans churned at higher rates. 2. Exploring distributions and correlations of numeric variables like account length, day minutes, and customer service calls with churn. Higher values in calls and minutes were linked to higher churn. 3. Using histograms, scatter plots, and other graphs to identify multivariate relationships, like finding customers with many calls but low minutes churned more. The analysis helped identify variables likely to predict churn for modeling without pre

1. ผู้ช่วยศาสตราจารย์จิรัฎฐา ภูบุญอบ ( jiratta . [email_address] . ac . th, 08-9275-9797 ) EXPLORATORY DATA ANALYSIS 3

25. 5. Exploring Numeric Variables (cont’d)