Hasty Generalization Fallacy – Definition & Examples

20.12.23 Fallacies Time to read: 7min

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Fallacies are common errors in reasoning that undermine the logic of an argument. In the realm of logical fallacies, the hasty generalization fallacy stands out for its appearance in everyday arguments. They typically arise from overgeneralizations or misinterpretations, leading to flawed conclusions. This article will shed light on the psychology behind it and how our minds often lead us to make these quick, yet flawed, judgments.

Hasty generalization fallacy in a nutshell

Hasty generalization, in a nutshell, is a logical fallacy where someone draws a broad conclusion based on insufficient or limited evidence. Instead of looking at a representative sample or gathering enough data, they make a sweeping generalization that may not be accurate or justified. It’s like making a big assumption about whole and unfair conclusions.

Definition: Hasty Generalization Fallacy

The hasty generalization fallacy (also known as the overgeneralization fallacy, faulty generalization, or argument from small numbers) is a logical fallacy or reasoning error. It occurs when a claim is made based on a sample that is too small to substantiate the claim adequately. The adequacy of a sample size in supporting a claim varies depending on the nature of the claim itself. More specifically, it is an informal logical fallacy where the logical disconnect occurs in the argument’s content, and not its structure. Delving deeper, the hasty generalization fallacy falls under the category of defective induction. It involves drawing a flawed conclusion from the evidence presented, indicating a disconnect in the logical progress of induction.

In other words: you are jumping to conclusions.


Imagine a student who takes a few mathematics tests and scores poorly on them. Based on these results, the student concludes, “I’m terrible at all mathematics.” The student is making a broad claim about their overall ability in mathematics based on a limited number of tests. This is without considering other factors like the difficulty of the tests, the topics covered, or their performance in different areas of mathematics. This conclusion is hastily drawn from insufficient pieces of evidence and does not accurately represent the student’s true mathematical abilities.

How does the hasty generalization fallacy work?

The hasty generalization fallacy begins when someone uses a very small sample size or selects data that is not representative of the overall population (or group) they are making a generalization about. In other words, it involves making a generalization about a larger population or group based on limited or biased evidence.

This hasty generalization fallacy typically operates as illustrated below:

  1. Limited data: Person A observes only a few examples, that are too small to represent a whole population.
  2. Overgeneralization: Person A makes a general statement or conclusion based on this limited data.
  3. Extrapolation: Person A extends the conclusion to make a broad generalization about the entire group.

In other words: If it is correct in this case, then it has to be in every case.


Illogical: I’ve met a group of Polish tourists at the airport and they were very rude. Therefore, people from Poland are generally rude.

Logical: I’ve met a group of Polish tourists at the airport who were rude, but I realize this is not enough to judge every individual from this country. People’s behavior can vary widely.

Unlike formal fallacies, which are irreparable in their logical structure, informal fallacies can be remedied by adjusting the language used to form coherent and logical statements. Recognizing an informal fallacy can be straightforward: maintain the structure of the argument but replace its content with a logically coherent statement. If the argument still seems reasonable, it’s likely an informal fallacy.

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Hasty generalization vs. faulty generalization

The terms “hasty generalization” and “faulty generalization” are often used interchangeably in discussions of logical fallacies, but they can be distinguished based on the nuances in their definitions and applications.

Hasty Generalization

The hasty generalization fallacy occurs when a conclusion is made about a whole group based on an insufficiently small or representative sample. The key aspect here is the “haste” – coming to a quick conclusion without considering all the necessary or relevant evidence.


You conclude that all smartphones are fragile because of the two models that you owned broke easily.

Faulty Generalization

Faulty generalization is a broader term that includes any conclusion drawn from insufficient or inappropriate evidence. It covers a range of fallacies where the generalization is incorrect due to the nature of the logic used, not just the size of the sample. Hasty generalization is a specific type of faulty generalization.


You are assuming a dietary supplement works for all health issues because it helped with one specific ailment.

Essentially, every hasty generalization is a faulty generalization, but not every faulty generalization is “hasty” as the latter covers any conclusion drawn from any insufficient evidence.

The distinction is subtle, but what sets the hasty generalization fallacy apart is the tendency of the arguer to quickly jump to a conclusion on a subject without fully considering the variety of factors that might undermine the conclusion.

Distinction to other fallacies

The distinction between the hasty generalization fallacy and other fallacies like cherry-picking and anecdotal evidence lies in the specific way each fallacy misuses evidence. Understanding the differences is crucial in critical thinking and logical reasoning. Below, you’ll find a breakdown of their differences:

Hasty generalization

The hasty generalization fallacy occurs when someone draws a conclusion based on insufficient or non-representative samples. The key element is the unrepresentative sample.


If you see a group of football player sneeze and conclude, “all football players have allergies.”


Cherry-picking (or selective evidence) involves evidence that supports one’s argument while ignoring evidence that contradicts it. The key element in this fallacy is the selective presentation of evidence.


If you are citing only studies that support a particular product’s effectiveness, while ignoring numerous studies that show no benefits or harmful effects.

Anecdotal evidence

This fallacy happens when conclusions are based on personal experiences rather than from broader, more systematic evidence. The key element here is the reliance on personal instances as representative of the norm.


Believing that a specific diet is effective for weight loss just because your neighbor lost weight on it and ignoring a broader scientific research on the effectiveness of this diet.

How to avoid the hasty generalization fallacy

The hasty generalization fallacy is significant as it leads to poor decision-making, negatively impacts communication and relationships, and undermines the integrity of arguments.

In academic writing, such as research papers or academic essays, making baseless logical claims can undermine the arguments you are making. It may indicate that you haven’t done enough research to support your assertions. Hasty generalizations are invalid statements that should not be used in your writing. Even if the generalization turns out to be somewhat accurate or even entirely accurate, it’s still not backed up by solid and sufficient evidence. This fallacy can be avoided by researching thoroughly and using reliable sources.


The hasty generalization fallacy is also known as the faulty generalization or argument from small numbers and occurs when someone draws a general conclusion based on limited data that is too small to represent a whole group or population. It is an informal logical fallacy that leads us to conclusions that are not supported by sufficient data or reliable sources.

Example of the hasty generalization fallacy

Imagine a person who tries a new brand of smartphone and experiences some technical difficulties with it. If they conclude, “All smartphones from this brand are defective and unreliable,” they are committing a hasty generalization. In this example, the person is basing their judgment of the products from this company on a single experience with one device. This single experience does not represent sufficient evidence to represent this company’s devices adequately.

This hasty generalization fallacy typically operates like this:

  1. Small sample from the population
  2. Conclusion based on this small sample
  3. Extrapolate the conclusion to the population

In academic writing, hasty generalizations can seriously undermine the credibility and validity of an argument, as it demands rigorous analysis and well-supported claims. You can avoid the hasty generalization fallacy in your writing by researching thoroughly and using reliable sources.

The hasty generalization fallacy specifically deals with conclusions made from inadequate sample sizes or unrepresentative data. Other fallacies, like ad hominem fallacy or slippery slope fallacy, involve different kinds of flawed reasoning or argumentation tactics.

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