Which of the following is the primary purpose of exploratory data analysis (ED

The primary purpose of exploratory data analysis (EDA) is to understand the main characteristics of a dataset by visually and statistically summarizing it. EDA helps identify patterns, trends, and relationships in the data, uncover outliers, and discover data errors or inconsistencies. This process is crucial before applying any modeling techniques, as it helps analysts gain insights into the data’s structure and informs the next steps in the analysis. EDA employs a range of techniques, including summary statistics, visualizations (such as histograms, box plots, scatter plots), and correlation analysis. It does not test hypotheses or make predictions but lays the foundation for further analysis. Why Other Options Are Incorrect: • A: Testing hypotheses is done through inferential statistics and hypothesis testing, not EDA. • C: Building a predictive model is typically the next step after performing EDA, not the main purpose of EDA itself. • D: Data storage and database decisions are made in the data management phase, not as part of EDA. • E: Reporting findings is a communication step that follows after conducting EDA and other analysis. EDA focuses on data exploration rather than presenting results.