5.3. Statistical Analysis and Feature Relationships

Summary statistics provide a useful first look at a dataset, but they rarely tell the full story. To understand how data represents a problem, we must examine how features are distributed, how they relate to one another, and how individual examples compare across multiple dimensions.

In this section, we move beyond isolated statistics and focus on relationships within the data. We begin by studying the distribution and behavior of individual features, then extend this analysis to interactions between features using correlation and visualization techniques. Finally, we introduce formal measures of similarity and distance to compare data points and explore structure in high-dimensional spaces.

Some of the methods introduced here assume reasonably clean and well-structured data. We revisit parts of this analysis after Data Wrangling, once missing values, inconsistencies, and outliers have been addressed.