SECAI Core · phase 1 of 15
Statistical learning
Developing mathematical models to explain and predict data behavior
The Explain card
- Plain English
- Statistical learning means building mathematical models that explain how data behaves and predict what it will do next. It is the maths underneath most machine learning.
- Example
- An intrusion detection tool fits a model to months of normal network traffic volumes, then raises an alert when tonight's outbound traffic falls far outside the predicted range.
- Why it matters
- Models built on statistics inherit the assumptions of the data. Skewed, stale or manipulated samples produce confident predictions that are quietly wrong, which attackers can exploit and defenders can misread.
- Hook
- A model is only as honest as the numbers it was fitted to.
Where it sits in the deck
Phase 1: What AI Is: Core Concepts and Paradigms
You cannot secure, govern, or attack something you cannot define — establish what AI actually is before any other concept can land.
