PLEASE LEARN HOT TO FUKIN ARGUE BEFORE YOU START NAME CALLING: AND JUST AS AN FYI, EDUCATED PERSON ACCEPTS OTHERS PEOPLE OPINIONS WITHOUT NAME CALLING. AND READ THIS, MIGHT HELP YOU OPEN UP YOUR CLOSED MIND. Post-hoc ergo propter hoc This is perhaps the most common of logical fallacies. It follows the basic format of A preceded B, therefore A caused B, and therefore assumes cause and effect for two events just because they are temporally related (the Latin translates to “after this, therefore because of this”). This logical fallacy is frequently invoked when defending various forms of alternative medicine – I was sick, I took treatment A, I got better, therefore treatment A made me better. This is a logical fallacy because it is possible to have recovered from an illness without any treatment. Confusing correlation with causation This is similar to the post-hoc fallacy in that it assumes cause and effect for two variables simply because they occur together. This fallacy is often used to give a statistical correlation a causal interpretation. For example, during the 1990’s both religious attendance and illegal drug use have been on the rise. It would be a fallacy to conclude that therefore, religious attendance causes illegal drug use. It is also possible that drug use leads to an increase in religious attendance, or that both drug use and religious attendance are increased by a third variable, such as an increase in societal unrest. It is also possible that both variables are independent of one another, and it is mere coincidence that they are both increasing at the same time. This fallacy, however, has a tendency to be abused, or applied inappropriately, to deny all statistical evidence. In fact this constitutes a logical fallacy in itself, the denial of causation. This abuse takes two basic forms. The first is to deny the significance of correlations that are demonstrated with prospective controlled data, such as would be acquired during a clinical experiment. The problem with assuming cause and effect from mere correlation is not that a causal relationship is impossible, it’s just that there are other variables that must be considered and not ruled out a-priori.
Posted on: Wed, 11 Sep 2013 16:09:50 +0000
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