: Use data-driven generation to validate initial assumptions.
2 Exploratory Data Analysis (EDA) – STAT 508 - Statistics Online Exploratory Data Analysis
: Detect outliers or impossible values (e.g., negative age) that could skew results. : Use data-driven generation to validate initial assumptions
Exploratory Data Analysis (EDA) is a creative and iterative process used to understand a dataset's main characteristics, often through visual methods, before formal modeling begins. It acts as a "storytelling" phase where analysts uncover patterns, spot anomalies, and test hypotheses. The Core Objectives of EDA often through visual methods
: Identify trends and relationships between variables.
: Verify if data meets the requirements for specific statistical methods, such as normal distribution. A Standard 5-Step EDA Workflow
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