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Hick's Law Calculator

Estimate how long users need to make a decision based on the number of choices. T = b × log₂(n + 1) – adjust the variables and see the growth curve in real time.

choices
15101520
ms

Decision time at 4 choices

348ms(0.35s)

T = 150 × log₂(4 + 1) ≈ 348ms

Within Miller's optimal range of 7 ± 2 items – comfortable.

Growth curve – 1 to 4 choices

1
150ms
2
238ms
3
300ms
4
348ms
Common scenarios
1 item150msSingle action button
2 items238msBinary toggle or split button
4 items348msQuick-action menu or tab bar
8 items475msStandard navigation menu
16 items613msComplex dropdown list

Why Hick's Law Shapes UX Design

William Edmund Hick and Ray Hyman independently established in 1952 that decision time increases logarithmically – not linearly – with the number of choices. This is a counterintuitive finding. Doubling the number of options does not double decision time; it adds roughly one more unit of processing. The logarithmic relationship is what makes Hick's Law practical for interface design: even large menus are manageable, as long as choices are organized, predictable, and well-labeled.

In practice, every navigation menu, dropdown, toolbar, and onboarding flow is a direct application of this law. A 12-item navigation bar takes roughly 3× longer to scan than a 4-item one. A settings page with 40 options can paralyze users who came in with a clear goal. The goal of IA (information architecture) is not minimizing choices – it's minimizing the perceived effort of choosing. Grouping, visual hierarchy, defaults, and search are all strategies that manipulate the effective n the user must evaluate at any moment.

The Miller's Law warning at n > 7 connects to a separate but related finding: human working memory holds 7 ± 2 chunks simultaneously. When users must evaluate more than 7 ungrouped options, they must rely on deliberate scanning rather than pattern recognition – which is slower, more error-prone, and more fatiguing. This is why chunking navigation into logical groups (even with more total items) often outperforms flat lists. The cognitive load factor (×1.5) in this tool approximates the additional time cost when choices are unfamiliar, unlabeled, or require reading rather than recognizing.

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