Joint effect is a logical fallacy of causation in which two phenomena that have a common cause are thought to be cause and effect themselves. A logical fallacy is an error in logical argument which is independent of the truth of the premises. ... Fallacies of questionable cause, also known as causal fallacies, non causa pro causa (non-cause for cause in Latin) or false cause, are informal fallacies where a cause is incorrectly identified. ...

Consider the classic example: Ice cream consumption increases during the summer months. Murder rates also increase during the summer months. Therefore, ice cream consumption causes murder. Alternatively, committing murder causes (leads to) ice cream consumption. Missing image Ice cream is often served on a stick Boxes of ice cream are often found in stores in a display freezer. ...

Once this causation fallacy is believed, it may lead to the crafting of ideas to explain the 'causation'. For example, perhaps chemicals within the ice cream interact with the consumer's neurotransmitters, so as to lead to aggressive, sometimes-murderous behavior. Alternatively, perhaps the neurotransmitters released during the act of murder lead to cravings that can be satisfied by high-fat content, sweet foods.

At the root of this fallacy is that, indeed, ice cream consumption and murder rates are highly correlated. Now, does ice cream incite murder or does murder increase the demand for ice cream? Neither: they are joint effects of a common cause, namely, hot weather during the summer season. In probability theory and statistics, correlation, also called correlation coefficient, is a numeric measure of the strength of linear relationship between two random variables. ...

This is a special case of correlation implies causation. In statistics, the common cause is called a confounding factor and this fallacy is called a spurious relationship. Correlation implies causation, also known as cum hoc ergo propter hoc (Latin for with this, therefore because of this) and false cause, is a logical fallacy by which two events that occur together are claimed to be cause and effect. ... Statistics is a broad mathematical discipline which studies ways to collect, summarize and draw conclusions from data. ... In statistics, a confounding factor is a factor which is the common cause of two things that may falsely appear to be in a causal relationship. ... In statistics, a spurious relationship (or, sometimes, spurious correlation) is a mathematical relationship in which two occurrences have no logical connection, yet it may be implied that they do, due to a certain third, unseen factor (referred to as a confounding factor or lurking variable). The spurious relationship gives an...

External links

• Stephen's Guide: Joint effect