Random Assignment

“A well-run lottery can make groups comparable without knowing every factor that separates them.”

01 / PLAINLY

What it means, plainly

Random assignment uses chance to place participants into conditions. It aims to prevent initial differences from following a systematic choice.

02 / CONTEXT

A little more

Random assignment uses chance to decide who receives each condition. On average it balances known and unknown factors, although any particular sample can still be imbalanced.

03 / WHY IT MATTERS

Why it matters

It makes a later difference more plausibly attributable to the compared conditions rather than to how the groups were formed.

04 / EXAMPLE

A familiar example

A generator assigns participants to two interface versions before their completion rates are measured.

05 / LIMIT

What it does not mean

Random does not mean haphazard, and randomization does not fix attrition, poor measurement, or noncompliance.

06 / NOTICE

Notice it in your day

Imagine twelve participants and two task versions. Design a simple lottery to assign them, then explain how hand-picking would differ.

FINAL NOTE

The idea worth keeping

Distinguish random population sampling from random assignment to conditions.

QUESTIONS / 02

Questions people still have

What does random assignment decide?

It uses chance to decide which study condition each participant receives.

Does it guarantee perfectly matched groups?

No. It balances factors on average, but a particular sample may still be uneven.