Essential Statistics for Data Science · Part 1 of 4
Statistics is at the heart of data science. Whether you're exploring raw data or building predictive models, fluency in the fundamentals is what lets you move from "the numbers say X" to a defensible, falsifiable claim.
This first post in the series lays out the foundational ideas: what statistics actually is, why it matters for modern ML, the difference between descriptive and inferential reasoning, and the bridge to causal inference. It's the scaffolding the rest of the series builds on.