Exploratory data analysis is primarily about

• A. Finding new features in a data set
• B. Making forecasts
• C. Identifying patterns
• D. Confirming a hypothesis

Answer: (C)

Exploratory data analysis is about uncovering patterns and relationships in the data through visualizations and summary statistics. By examining distributions, looking at histograms, box plots, and scatter plots, you can see how variables interact, spot outliers, and detect any natural groupings or trends. This open-ended exploration helps you understand what the data are telling you before you apply models or tests. It’s not primarily about forecasting future values (that’s predictive analytics) or about confirming a pre-existing hypothesis (that’s confirmatory analysis). It also isn’t mainly about creating new features; feature engineering can follow once you’ve understood the data, but the central aim of EDA is to reveal patterns and structure that guide subsequent steps.