False Cause Fallacy | Definition & Examples
A false cause fallacy occurs when someone incorrectly assumes that a causal relation exists between two things or events. This is an improper conclusion because either such a relationship does not exist or the evidence in support of it is insufficient.
This type of reasoning error can lead to superstitious beliefs about the causes of various phenomena and events, a poor understanding of reality, and an inability to address root causes of problems.
What is false cause fallacy?
The false cause fallacy, also known as causal fallacy or non causa pro causa (Latin for “non-cause for cause”) occurs when someone incorrectly concludes that one thing is the cause of another.
Causal fallacies are informal fallacies because the error lies in the content of the argument, rather than its logical structure. To identify the flawed reasoning one has to look at both the content and the context of the argument. In the case of the false cause fallacy, the problem is in the improper reasoning about cause-and-effect relationships.
This can be due to a number of reasons, such as mistaking correlation or co-occurrence for causation, oversimplifying the real causes of an event, or reversing the direction of cause and effect. However, it’s important to note that the occurrence of a false cause fallacy does not necessarily mean the conclusion is false, but only that no adequate proof has been given.
What are different types of false cause fallacy?
Because “false cause fallacy” is an umbrella term describing various mistakes in causal reasoning, there are several different types or variations.
Post hoc ergo propter hoc fallacy
Post hoc ergo propter hoc fallacy (Latin for: “after this, therefore because of this”) or post hoc fallacy occurs when we incorrectly conclude that the temporal sequence of two events is proof that one caused the other (e.g., “if A happened before B, then A must have caused B”).
The post hoc fallacy underlies many superstitions and rituals around sports.
Cum hoc ergo propter hoc
Cum hoc ergo propter hoc fallacy (Latin for: “with this, therefore because of this”) is the assumption that because two things (often) happen simultaneously, one causes the other.
This type of causal fallacy ignores the possibility that the two events or variables co-occurring could be a coincidence or that there could be a separate, unidentified cause.
Here, the person arguing that sleeping with one’s shoes on causes headaches is likely ignoring a third factor that explains both (e.g., going to bed drunk).
Post hoc fallacy and cum hoc ergo propter hoc fallacy are quite similar, but there is a subtle difference between the two regarding the timing of events:
- In post hoc fallacy, one event is interpreted to be the cause of a later event because it occurred earlier.
- In cum hoc ergo propter hoc fallacy, two events occur simultaneously.
Non causa pro causa
Non causa pro causa (Latin for “non-cause for cause”) is a catch-all term that describes any type of fallacy in which we mistake a false cause of an event for the real cause. “Non causa pro causa” is the same fallacy as “false cause.” It’s used to describe the previous two fallacies, as well as other less typical variations, such as:
- Fallacy of the single cause is the assumption that an event has a single cause, when it actually has a variety of causes. Here, causal relationships are oversimplified. For example, when a large company goes bankrupt, people may ascribe this to poor financial management. However, major events like this usually happen as a result of multiple causes (e.g., takeover by another company, fierce competition, increased costs).
- Reverse causation fallacy occurs when the direction of cause and effect is reversed. In other words, we assume that A causes B, without realising that B actually causes A. For example, when the streetlights turn on (A), the sun begins to set (B). Reverse causation would lead us to assume that the street lights (A) cause the sun to set (B), while it’s actually the other way around.
In this example, there’s no evidence of a direct causal link between the necklace and the person’s luck. Other factors likely influenced the outcomes (e.g., random chance).
False cause fallacy examples
False cause fallacy often arises in discussions about cause-and-effect relationships between certain types of music, video games, or movies and behavior issues.
Here, the speaker commits a false cause fallacy by concluding that listening to heavy metal directly leads to violent behavior. This is an oversimplification because the relationship between behavior and music preference is far more nuanced and other factors may be at play (e.g., psychological factors, individual predispositions, environmental factors).
Furthermore, the quoted study merely points towards a possible correlation between music and behavior, not a definite cause-and-effect relationship.
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Frequently asked questions about false cause fallacy
- How can I identify a false cause fallacy in an argument?
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To identify a false cause fallacy, you need to carefully analyse the argument:
- When someone claims that one event directly causes another, ask if there is sufficient evidence to establish a cause-and-effect relationship.
- Ask if the claim is based merely on the chronological order or co-occurrence of the two events.
- Consider alternative possible explanations (are there other factors at play that could influence the outcome?).
By carefully analysing the reasoning, considering alternative explanations, and examining the evidence provided, you can identify a false cause fallacy and discern whether a causal claim is valid or flawed.
- What are some examples of false cause fallacy?
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False cause fallacy examples include:
- Believing that wearing your lucky jersey will help your team win
- Thinking that everytime you wash your car, it rains
- Claiming that playing video games causes violent behavior
In each of these examples, we falsely assume that one event causes another without any proof.
- What’s the difference between correlation and causation?
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Correlation describes an association between variables: when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.
Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.
While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy.
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Nikolopoulou, K. (2023, July 05). False Cause Fallacy | Definition & Examples. Scribbr. Retrieved 11 November 2024, from https://www.scribbr.co.uk/fallacy/the-false-cause-fallacy/
