In one line: The first number we see drags our judgement towards it — even when it's irrelevant.
Anchoring bias is a cognitive-approach term. Once an anchor is set, we adjust away from it — but usually not far enough. It is a clear case of the concept of bias.
A £200 jumper marked down to £80 feels cheap; the same jumper first seen at £80 feels ordinary. The starting figure — the anchor — shifts what seems reasonable, without us noticing.
Memory hook: First number sticks. We anchor to it and don't drift far enough away.
Free preview
This is the free notes preview
You're reading the free notes. Aimnova Pro unlocks the full study experience — and you can try it free for 7 days:
- FlashcardsLock in vocabulary and key terms with spaced repetition.
- Practice questionsAnswer exam-style questions and get instant AI marking.
- Mock exams & past-paper vaultSit full mocks and see exactly how examiners award marks.
- Personalised study planA daily plan built around your exam date and weak areas.
Key idea: An anchor is a starting point; we adjust from it, but the adjustment is usually too small, so the anchor still shapes the final judgement.
Anchoring step by step
Meet the anchor
A first value lands — a price, an estimate, a number even randomly given.
Adjust from it
We move our estimate up or down from the anchor, treating it as a starting reference.
Stop too soon
The adjustment is too small, so the final answer stays pulled towards the anchor.
Anchor · Adjust too little · Biased answer
Take negotiating a used car. If the seller opens at £9,000, the buyer's counter-offer and final price sit higher than if the seller had opened at £6,000 — even for the same car. The opening figure anchored the whole negotiation. This is the concept of bias at work.
Go further — higher-level insight: Anchors work even when they're obviously random. Studies show people's estimates shift towards a number they know was produced by a spin of a wheel. That is what makes anchoring such striking evidence that judgement is not purely rational.
Stop wasting time on topics you know
Our AI identifies your weak areas and focuses your study time where it matters. No more overstudying easy topics.
Key idea: Anchoring is robust and practically important, but its size depends on context and expertise.
So anchoring is a strong, well-replicated bias with clear real-world uses (and misuses, like inflated 'original' prices), but a good evaluation notes it varies in strength and is more a reliable pattern than a complete theory of why.
Watch out: Awareness isn't enough. Simply knowing about anchoring doesn't remove it. The better defence is generating your own estimate first, before you see anyone else's number.