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Cat: Who will you vote for president of the United States in the next election? Dog: I can't decide between the Republican or the Democrat because I don't like either of them. Cat: Then why not vote for a third party candidate? Dog: I wouldn't do that, they don't have any chance of winning.
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Confusing Cause and Effect
AKA Questionable Cause, Reversing Causation

Category: Fallacies of Presumption → Casual Fallacies

Confusing Cause and Effect is a fallacy that has the following general form:

  1. A and B regularly occur together.
  2. Therefore A is the cause of B. This fallacy requires that there not be, in fact, a common cause that actually causes both A and B.
This fallacy is committed when a person assumes that one event must cause another just because the events occur together. More formally, this fallacy involves drawing the conclusion that A is the cause of B simply because A and B are in regular conjunction (and there is not a common cause that is actually the cause of A and B). The mistake being made is that the causal conclusion is being drawn without adequate justification.

In some cases it will be evident that the fallacy is being committed. For example, a person might claim that an illness was caused by a person getting a fever. In this case, it would be quite clear that the fever was caused by illness and not the other way around. In other cases, the fallacy is not always evident. One factor that makes causal reasoning quite difficult is that it is not always evident what is the cause and what is the effect. For example, a problem child might be the cause of the parents being short tempered or the short temper of the parents might be the cause of the child being problematic. The difficulty is increased by the fact that some situations might involve feedback. For example, the parents' temper might cause the child to become problematic and the child's behavior could worsen the parents' temper. In such cases it could be rather difficult to sort out what caused what in the first place.

In order to determine that the fallacy has been committed, it must be shown that the causal conclusion has not been adequately supported and that the person committing the fallacy has confused the actual cause with the effect. Showing that the fallacy has been committed will typically involve determining the actual cause and the actual effect. In some cases, as noted above, this can be quite easy. In other cases it will be difficult. In some cases, it might be almost impossible. Another thing that makes causal reasoning difficult is that people often have very different conceptions of cause and, in some cases, the issues are clouded by emotions and ideologies. For example, people often claim violence on TV and in movies must be censored because it causes people to like violence. Other people claim that there is violence on TV and in movies because people like violence. In this case, it is not obvious what the cause really is and the issue is clouded by the fact that emotions often run high on this issue.

While causal reasoning can be difficult, many errors can be avoided with due care and careful testing procedures. This is due to the fact that the fallacy arises because the conclusion is drawn without due care. One way to avoid the fallacy is to pay careful attention to the temporal sequence of events. Since (outside of Star Trek), effects do not generally precede their causes, if A occurs after B, then A cannot be the cause of B. However, these methods go beyond the scope of this program.

All causal fallacies involve an error in causal reasoning. However, this fallacy differs from the other causal fallacies in terms of the error in reasoning being made. In the case of a Post Hoc fallacy, the error is that a person is accepting that A is the cause of B simply because A occurs before B. In the case of the Fallacy of Ignoring a Common Cause A is taken to be the cause of B when there is, in fact, a third factor that is the cause of both A and B. For more information, see the relevant entries in this program.

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15
Appeal to Popularity
Ad Populum

Category: Fallacies of Relevance (Red Herrings)

The Appeal to Popularity has the following form:

  1. Most people approve of X (have favorable emotions towards X).
  2. Therefore X is true.
The basic idea is that a claim is accepted as being true simply because most people are favorably inclined towards the claim. More formally, the fact that most people have favorable emotions associated with the claim is substituted in place of actual evidence for the claim. A person falls prey to this fallacy if he accepts a claim as being true simply because most other people approve of the claim.

It is clearly fallacious to accept the approval of the majority as evidence for a claim. For example, suppose that a skilled speaker managed to get most people to absolutely love the claim that 1+1=3. It would still not be rational to accept this claim simply because most people approved of it. After all, mere approval is no substitute for a mathematical proof. At one time people approved of claims such as "the world is flat", "humans cannot survive at speeds greater than 25 miles per hour", "the sun revolves around the earth" but all these claims turned out to be false.

This sort of "reasoning" is quite common and can be quite an effective persuasive device. Since most humans tend to conform with the views of the majority, convincing a person that the majority approves of a claim is often an effective way to get him to accept it. Advertisers often use this tactic when they attempt to sell products by claiming that everyone uses and loves their products. In such cases they hope that people will accept the (purported) approval of others as a good reason to buy the product.

This fallacy is vaguely similar to such fallacies as Appeal to Belief and Appeal to Common Practice. However, in the case of an Ad Populum the appeal is to the fact that most people approve of a claim. In the case of an Appeal to Belief, the appeal is to the fact that most people believe a claim. In the case of an Appeal to Common Practice, the appeal is to the fact that many people take the action in question.

This fallacy is closely related to the Appeal to Emotion fallacy, as discussed in the entry for that fallacy.

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319
Appeal to Fear
Ad Baculum

AKA Scare Tactics, Appeal to Force

Category: Fallacies of Relevance (Red Herrings) → Distracting Appeals

The Appeal to Fear is a fallacy with the following pattern:

  1. Y is presented (a claim that is intended to produce fear).
  2. Therefore claim X is true (a claim that is generally, but need not be, related to Y in some manner).
This line of "reasoning" is fallacious because creating fear in people does not constitute evidence for a claim.

It is important to distinguish between a rational reason to believe (RRB) (evidence) and a prudential reason to believe(PRB) (motivation). A RRB is evidence that objectively and logically supports the claim. A PRB is a reason to accept the belief because of some external factor (such as fear, a threat, or a benefit or harm that may stem from the belief) that is relevant to what a person values but is not relevant to the truth or falsity of the claim. For example, it might be prudent to not fail the son of your department chairperson because you fear he will make life tough for you. However, this does not provide evidence for the claim that the son deserves to pass the class.

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5
Appeal to Flattery
AKA Apple Polishing, various 'colorful' expressions

Category: Fallacies of Relevance (Red Herrings) → Distracting Appeals

An Appeal to Flattery is a fallacy of the following form:

  1. Person A is flattered by person B.
  2. Person B makes claim X.
  3. Therefore X is true.
The basic idea behind this fallacy is that flattery is presented in the place of evidence for accepting a claim. This sort of "reasoning" is fallacious because flattery is not, in fact, evidence for a claim. This is especially clear in a case like this: "My Bill, that is a really nice tie. By the way, it is quite clear that one plus one is equal to forty three."

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1
Fallacy of Division
Category: Fallacies of Ambiguity

The fallacy of Division is committed when a person infers that what is true of a whole must also be true of its constituents and justification for that inference is not provided. There are two main variants of the general fallacy of Division:

The first type of fallacy of Division is committed when 1) a person reasons that what is true of the whole must also be true of the parts and 2) the person fails to justify that inference with the required degree of evidence. More formally, the "reasoning" follows this sort of pattern:

  1. The whole, X, has properties A, B, C, etc.
  2. Therefore the parts of X have properties A,B,C, etc.
That this line of reasoning is fallacious is made clear by the following case: 4 is an even number. 1 and 3 are parts of 4. Therefore 1 and 3 are even.

It should be noted that it is not always fallacious to draw a conclusion about the parts of a whole based on the properties of the whole. As long as adequate evidence is provided in the argument, the reasoning can be acceptable. For example, the human body is made out of matter and it is reasonable to infer from this that the parts that make up the human body are also made out of matter. This is because there is no reason to believe that the body is made up of nonā€material parts that somehow form matter when they get together.

The second version of the fallacy of division is committed when a person 1) draws a conclusion about the properties of individual members of a class or group based on the collective properties of the class or group and 2) there is not enough justification for the conclusion. More formally, the line of "reasoning" is as follows:

  1. As a collective, group or class X has properties A,B,C, etc.
  2. Therefore the individual members of group or class X have properties A,B,C, etc.
That this sort of reasoning is fallacious can be easily shown by the following: It is true that athletes, taken as a group, are football players, track runners, swimmers, tennis players, long jumpers, pole vaulters and such. But it would be fallacious to infer that each individual athlete is a football player, a track runner, a swimmer, a tennis player, a swimmer, etc.

It should be noted that it is not always fallacious to draw a conclusion about an individual based on what is true of the class he/she/it belongs to. If the inference is backed by evidence, then the reasoning can be fine. For example, it is not fallacious to infer that Bill the Siamese cat is a mammal from the fact that all cats are mammals. In this case, what is true of the class is also true of each individual member.

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20
Hasty Generalization
AKA Fallacy of Insufficient Statistics, Fallacy of Insufficient Sample, Leaping to A Conclusion, Hasty Induction

Category: Fallacies of Presumption

This fallacy is committed when a person draws a conclusion about a population based on a sample that is not large enough. It has the following form:

  1. Sample S, which is too small, is taken from population P.
  2. Conclusion C is drawn about Population P based on S.
The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization:
  1. X% of all observed A's are B's.
  2. Therefore X% of all A's are B's.
The fallacy is committed when not enough A's are observed to warrant the conclusion. If enough A's are observed then the reasoning is not fallacious.

Small samples will tend to be unrepresentative. As a blatant case, asking one person what she thinks about gun control would clearly not provide an adequate sized sample for determining what Canadians in general think about the issue. The general idea is that small samples are less likely to contain numbers proportional to the whole population. For example, if a bucket contains blue, red, green and orange marbles, then a sample of three marbles cannot possible be representative of the whole population of marbles. As the sample size of marbles increases the more likely it becomes that marbles of each color will be selected in proportion to their numbers in the whole population. The same holds true for things others than marbles, such as people and their political views.

Since Hasty Generalization is committed when the sample (the observed instances) is too small, it is important to have samples that are large enough when making a generalization. The most reliable way to do this is to take as large a sample as is practical. There are no fixed numbers as to what counts as being large enough. If the population in question is not very diverse (a population of cloned mice, for example) then a very small sample would suffice. If the population is very diverse (people, for example) then a fairly large sample would be needed. The size of the sample also depends on the size of the population. Obviously, a very small population will not support a huge sample. Finally, the required size will depend on the purpose of the sample. If Bill wants to know what Joe and Jane think about gun control, then a sample consisting of Bill and Jane would (obviously) be large enough. If Bill wants to know what most Australians think about gun control, then a sample consisting of Bill and Jane would be far too small.

People often commit Hasty Generalizations because of bias or prejudice. For example, someone who is a sexist might conclude that all women are unfit to fly jet fighters because one woman crashed one. People also commonly commit Hasty Generalizations because of laziness or sloppiness. It is very easy to simply leap to a conclusion and much harder to gather an adequate sample and draw a justified conclusion. Thus, avoiding this fallacy requires minimizing the influence of bias and taking care to select a sample that is large enough.

One final point: a Hasty Generalization, like any fallacy, might have a true conclusion. However, as long as the reasoning is fallacious there is no reason to accept the conclusion based on that reasoning.

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