After ≠ Because
Don’t mistake sequence for cause.
Someone might believe that performing a pre-game ritual helps their team win and avoid walking under ladders for fear it will bring bad luck. In both cases, they see causation where none exists.
Just because an event happens before another doesn’t mean the first event causes the second. Yet we tend to assume it does, a bias known as post hoc reasoning. It once helped our ancestors survive by spotting potential dangers quickly, like interpreting rustling in the bushes as a predator or smoke as a sign of fire. Better to make a false connection than miss a real threat. Nowadays, however, this bias makes us prone to jumping to conclusions when the link isn’t real.
Post hoc reasoning is like believing that performing a rain dance causes it to rain.
Getting causation wrong can have real consequences:
👉 Vaccines & health: Some parents noticed signs of autism after their children received vaccines and believed the shots caused it. In reality, autism symptoms often appear around the same age as routine vaccinations, so they mistook timing for cause. This misunderstanding led some to avoid vaccines, putting children at risk of preventable diseases.
👉 Technology & health: When brain tumors appeared in heavy cell phone users, some assumed the phones caused them because the tumors developed after frequent use. Research found no causal link, but mistaking timing for cause fueled fear and unnecessary anxiety.
👉 Health & medicine: Recovering from a cold after taking a homeopathic remedy can create the false impression that the treatment worked, since most colds improve naturally. This belief can lead to wasted money and ignoring effective care.
👉 Superstitions & belief: Some believe walking under ladders or seeing black cats causes bad luck, or that carrying lucky charms prevents it. In voodoo, when illness or misfortune follows a curse, it’s often taken as proof that the curse worked, even when there is no causal connection. These beliefs reinforce irrational fears and rituals.
👉 Politics: When outcomes shift soon after a new administration takes office, people often assume the leadership caused it. Supporters credit the government if unemployment falls, while opponents blame it if it rises. This oversimplifies complex realities and fuels polarization.
👉 Public health policy: Assuming that specific COVID-19 measures, like mask mandates or lockdowns, caused a drop in cases without considering other factors can be misleading. Natural infection trends or changes in testing may explain the decline, and overlooking them can give a false sense of confidence and obscure more effective strategies.
👉 Business & marketing: When sales rise after a new campaign, companies may assume the campaign caused the boost. Other factors, like seasonal demand or overlapping promotions, might be responsible instead. This can lead to misallocated budgets or repeated strategies that aren’t actually effective.
How to avoid the fallacy when stakes are high
For high-stakes decisions, such as those involving physical or emotional health, money, or safety, don’t act on assumptions based only on what happened before. Use these techniques to avoid falling into post hoc reasoning.
👉 Look for alternative causes: Consider other factors that could have caused the outcome. For example, if a marketing campaign is followed by a sales increase, think about seasonality, promotions, or other changes that might explain it.
👉 Check for repeated patterns: One instance doesn’t prove causation. Look for consistent results across multiple cases. For example, seeing sales rise once after a campaign doesn’t prove it works; check whether similar campaigns consistently produce the same effect.
👉 Use controlled comparisons: Whenever possible, compare what happens with and without the suspected cause. For example, if testing a new sales campaign, see how regions with the campaign perform compared with similar regions without it.
👉 Look for a plausible mechanism: Just because one event follows another doesn’t mean it caused the other; ask if there’s a reasonable way they could be connected. For example, someone might walk under a ladder and then have something bad happen, but there’s no plausible way the ladder caused the misfortune.
👉 Seek evidence beyond anecdotes: Personal stories can be misleading. For example, one person might lose weight after taking a new supplement, but broader studies may show it has no real effect.
🎉👏🎈
Lucky rituals don’t win games, and walking under ladders doesn’t cause bad luck. Understanding that sequence isn’t causation helps keep your thinking clear and your choices grounded in reality.
