OverclockedJesus Posted:

O RLY?

Then name them, please. Otherwise, I’ll just bumume you’re terrified of my intellect, and I will laugh at you.

Description of Begging the Question

Begging the Question is a fallacy in which the premises include the claim that the conclusion is true or (directly or indirectly) bumume that the conclusion is true. This sort of “reasoning” typically has the following form.

1. Premises in which the truth of the conclusion is claimed or the truth of the conclusion is bumumed (either directly or indirectly).

2. Claim C (the conclusion) is true.

This sort of “reasoning” is fallacious because simply bumuming that the conclusion is true (directly or indirectly) in the premises does not constitute evidence for that conclusion. Obviously, simply bumuming a claim is true does not serve as evidence for that claim. This is especially clear in particularly blatant cases: “X is true. The evidence for this claim is that X is true.”

Some cases of question begging are fairly blatant, while others can be extremely subtle.

escription of Burden of Proof

Burden of Proof is a fallacy in which the burden of proof is placed on the wrong side. Another version occurs when a lack of evidence for side A is taken to be evidence for side B in cases in which the burden of proof actually rests on side B. A common name for this is an Appeal to Ignorance. This sort of reasoning typically has the following form:

1. Claim X is presented by side A and the burden of proof actually rests on side B.

2. Side B claims that X is false because there is no proof for X.

In many situations, one side has the burden of proof resting on it. This side is obligated to provide evidence for its position. The claim of the other side, the one that does not bear the burden of proof, is bumumed to be true unless proven otherwise. The difficulty in such cases is determining which side, if any, the burden of proof rests on. In many cases, settling this issue can be a matter of significant debate. In some cases the burden of proof is set by the situation. For example, in American law a person is bumumed to be innocent until proven guilty (hence the burden of proof is on the prosecution). As another example, in debate the burden of proof is placed on the affirmative team. As a final example, in most cases the burden of proof rests on those who claim something exists (such as Bigfoot, psychic powers, universals, and sense data)

Description of Hasty Generalization

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 Bs.

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 determing 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 proprtion 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.