Cum Hoc Ergo Propter Hoc (False Cause)

78 False Cause : Cum Hoc Ergo Propter Hoc

Bertha Alvarez Manninen

People who eat Shredded Wheat tend to have healthy hearts.

Advertising campaign for Shredded Wheat breakfast cereal

In general, the false cause fallacy occurs when the “link between premises and conclusion depends on some imagined causal connection that probably does not exist” (Hurley 2015, 149). There are three different ways an argument can commit the false cause fallacy: post hoc ergo propter hoc; cum hoc ergo propter hoc; and ignoring common cause. We’ll deal with cum hoc ergo propter hoc here. Also see the chapters for post hoc ergo propter hoc (Chapter 80) and ignoring common cause (Chapter 79).

This Latin phrase literally translates to “with this, therefore because of this.” This fallacy occurs when one assumes a causal relationship between two events because they occurred simultaneously. Like the post hoc ergo propter hoc fallacy, this fallacy is guilty of trying to establish a causal connection between two events on dubious grounds. It is clear that two events can happen at the same time and yet there is no causal connection between them. Perhaps you purchased a car at the exact time when someone else crashed her car – clearly this does not mean that it was your purchase that caused the car accident to occur. In the above‐cited advertising campaign, “it does not explicitly state that there is any causal connection between eating Shredded Wheat and having a healthy heart, but it invites viewers of the advertisements to make the connection; the implication is there. Whether or not there is any such connection, the mere fact that the two things are correlated does not prove that there is such a connection” (Logical Fallacies 2009).

This fallacy most typically occurs when there appears to be a constant correlation between two events. For example, say that you trip and fall every time that Bill is around and therefore you conclude that Bill is bad luck. Or you seem to fail an exam every time you use a specific writing utensil and assume that the pen is somehow cursed. Here you have equated the constant correlation of two events with a causal connection without any additional evidence in support of causation.

The phrase “correlation does not imply causation” is often used in scientific and statistical circles to caution against concluding that a causal connection exists between two variables solely based on a correlation (even a constant one) between them. For example, some observational studies illustrated a correlation between women undergoing hormone replacement therapy (HRT) and having a low incidence of coronary heart disease. The conclusion drawn from this was that HRT led to a decreased risk of coronary heart disease. However, subsequent randomized trials illustrated the opposite – that there was an increased risk of coronary heart disease following HRT. One proposed explanation for the discrepancy was confounding in the observational studies: women undergoing HRT could differ in socioeconomic circumstances and health-related behavior from women who did not. These differences could help explain the observed association. When the correlation between two variables can be explained by appealing to a common third variable, this is called a “confounder.” As such “the protective effect of HRT found in previous observational studies was likely to be influenced by residual confounding. Inadequate adjustment for socioeconomic position from across the life course would be one source of this residual confounding” (Lawlor, Smith, and Ebrahim 2004, 465).

This is not to say, however, that consistent correlation between two events can never be indicative of causation. For the first half of the twentieth century, the tobacco industry denied that smoking directly increased one’s chances of lung cancer, dismissing the correlation between the two as non‐indicative of any causal relationship. However, in the 1950s, evidence accumulated supporting a causal relationship. The case illustrates why a causal conclusion depends on the wider evidence, rather than correlation alone. The way to avoid committing the cum hoc ergo propter hoc fallacy, therefore, is to study correlative relationships more carefully in order to decipher if an actual causal relationship exists rather than assuming the latter follows from the former.