science

Outcome bias

Outcome bias is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Outcome bias rather than just read about it. In short: The outcome bias is an error made in evaluating the quality of a decision when the outcome of that decision is already known. Specifically, the outcome effect occurs when the same "behavior produce[s] more ethical condemnation when it happen[s] to produce bad rather than good outcome, even if the outcome is determined by chance".

Key takeaways

Outcome bias belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Outcome bias to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Outcome bias from memory before moving on to harder problems.

Reference excerpt

The outcome bias is an error made in evaluating the quality of a decision when the outcome of that decision is already known. Specifically, the outcome effect occurs when the same "behavior produce[s] more ethical condemnation when it happen[s] to produce bad rather than good outcome, even if the outcome is determined by chance". While similar to the hindsight bias, the two phenomena are markedly different. Hindsight bias focuses on memory distortion to favor the actor, while the outcome bias focuses exclusively on weighting the outcome heavier than other pieces of information in deciding if a past decision was correct.

Overview One will often judge a past decision by its ultimate outcome instead of based on the quality of the decision at the time it was made, given what was known at that time. This is an error because no decision-maker ever knows whether or not a calculated risk will turn out for the best. The actual outcome of the decision will often be determined by chance, with some risks working out and others not. Individuals whose judgments are influenced by outcome bias are seemingly holding decision-makers responsible for events beyond their control. Baron and Hershey (1988) presented subjects with hypothetical situations in order to test this. One such example involved a surgeon deciding whether or not to do a risky surgery on a patient. The surgery had a known probability of success. Subjects were presented with either a good or bad outcome (in this case living or dying), and asked to rate the quality of the surgeon's pre-operation decision. Those presented with bad outcomes rated the decision worse than those who had good outcomes. "The ends justify the means" is an often-used aphorism to express the outcome effect when the outcome is desirable. This mistake occurs when currently available information is incorporated when evaluating a past decision. To avoid the influence of outcome bias, one would evaluate a decision by ignoring information collected after the fact and focusing on what the right answer is, or was at the time the decision was made. Outside of psychological experiments, the outcome bias has been found to be substantially present in real world situations. A study looking at the evaluation of football players' performance by coaches and journalists found that players' performance is judged to be substantially better—over a whole match—if the player had a lucky goal rather than an unlucky miss (after a player's shot hit one of the goal posts). Another study found that professional basketball coaches are "more likely to revise their strategy after a loss than a win... even when a loss was expected and even when failure is due to factors beyond the team's control." The outcome bias is closely related to the philosophical concept of moral luck as in both concepts, the evaluation of actions is influenced by factors that are not logically justifiable.

See also Deontology vs. teleology and consequentialism (ethical theories) Group attribution error Hindsight bias Historian's fallacy List of cognitive biases

References

Worked examples

Example 1 — a first encounter with Outcome bias

Start with the simplest possible case. Write down what Outcome bias claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Outcome bias before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Outcome bias ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Outcome bias

In research: Outcome bias appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Outcome bias in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Outcome bias is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cognitive biases, so understanding it makes those chapters shorter.
In everyday life: Look for Outcome bias outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Outcome bias in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Outcome bias means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Outcome bias out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Outcome bias in simple terms?

Why does Outcome bias matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Outcome bias?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Outcome bias.