MENTAL MODEL · M6286

Normalization

TechnicalHigh supportStatistics

Included

Version 1.0.0 · Updated 2026-07-30

CORE DEFINITION

Transform data with different dimensions and magnitudes (e.g., height and salary) to a common standard scale (e.g., 0 to 1) for comparison and weighting.

SCAFFOLDING EFFECT

psychology

Reduce cognitive load

Level the playing field. When evaluating employees (sales vs. R&D) or choosing between options (high risk/high return vs. low risk/low return), direct comparison is invalid. Normalization must be applied first to eliminate dimensional effects, enabling fair competition on the same scale.

anchor

Anchor fast decisions

Normalization refers to scaling data or vectors to a unified scale (e.g., [0,1], unit length, zero mean) according to certain rules, eliminating dimensional differences and stabilizing computation. Database normalization refers to eliminating redundant dependencies.

MINIMUM ACTION

In progress 0/4

Practice this model in one real situation:

Choose methods: min-max scaling, z-score, or unit vectors
compute statistics on training set and reuse
in databases, decompose tables according to normal forms to eliminate update anomalies
trade off denormalization based on task.

Check to track your progress (stored locally)

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Source support: Explicit

link
en.wikipedia.orghttps://en.wikipedia.org/wiki/NormalizationZH · Explicit
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