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Logical  Fallacy: a error in reasoning
  (adj)     (noun)

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Statement #163 Discussion

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Below is the statement as it appears with the fallacy marked as correct. You can see the totals of most frequent responses to this statement. And after reading the any discussion going on below, you can select your choice(s) for the correct answer. For now, whoever posts each statement can update corrections.
I just got cut off by the woman driver in front of me. Women can't drive.
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.

Click For Fallacy Description

 587 Total Answer Attempts   77%
 453 Correctly Popped Fallacies
 134 Incorrectly Un/Popped
posted by wikiworldorder     
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Most Common Responses

 
453 - Hasty Generalization
49 - Biased Generalization
9 - Post Hoc
8 - Ad Hominem
7 - Circumstantial Ad Hominem
6 - Genetic Fallacy
6 - Begging the Question
5 - False Dilemma
4 - Fallacy of Division
4 - Confusing Cause and Effect
4 - Poisoning the Well
3 - Ad Hominem Tu Quoque
3 - Fallacy of Composition
2 - Guilt by Association
2 - Appeal to Novelty
2 - Misleading Vividness
2 - Personal Attack
2 - Appeal to Tradition
2 - Appeal to Emotion
2 - Appeal to the Consequences of a Belief
1 - Appeal to Spite
1 - Relativist Fallacy
1 - Appeal to Ridicule
1 - Ignoring a Common Cause
1 - Appeal to Authority
1 - Peer Pressure
1 - Red Herring
1 - Appeal to Common Practice
1 - Appeal to Popularity
1 - Burden of Proof
1 - Middle Ground
1 - Slippery Slope

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i think you have a type o in your dialog cloud "I go cut off" LOL one thing after another = Post Hoc

4.6.15 16:15 by bruceh383@gmail.com
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  + Reply 1 comment downstream. Please read it before replying.

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Thanks for that catch! (Corrected)

4.6.15 18:53 by wikiworldorder
0      0

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