Hasty Generalization

Alias: Converse Fallacy of the Accident, or Converse Accident, for short (See Exposure, below)

Taxonomy: Logical Fallacy > Informal Fallacy > Weak Analogy > Unrepresentative Sample > Hasty Generalization

Quote…

It's a story, say, about the New York City public schools. In the first paragraph a parent, apparently picked at random, testifies that they haven't improved. Readers are clearly expected to draw conclusions from this. But it isn't clear why the individual was picked; it isn't possible to determine whether she's representative; and there's no way of knowing whether she knows what she's talking about. Calling on the individual man or woman on the street to make conclusive judgments is beneath journalistic dignity. If polls involving hundreds of people carry a cautionary note indicating a margin of error of plus-or-minus five points, what kind of consumer warning should be glued to a reporter's ad hoc poll of three or four respondents?

…Unquote

Source: Daniel Okrent, "13 Things I Meant to Write About but Never Did", New York Times, 5/22/2005

Example:

Of course your columnist Michele Slatalla was joking when she wrote about needing to talk with her 58-year-old mother about going into a nursing home. While I admire Slatalla's concern for her parents, and agree that as one approaches 60 it is wise to make some long-term plans, I hardly think that 58 is the right age at which to talk about a retirement home unless there are some serious health concerns. In this era, when people are living to a healthy and ripe old age, Slatalla is jumping the gun. My 85-year-old mother power-walks two miles each day, drives her car (safely), climbs stairs, does crosswords, reads the daily paper and could probably beat Slatalla at almost anything.

Source: Nancy Edwards, "Letters to the Editor", Time, 6/26/00

Analysis

Exposition:

In logic, "generalization" refers to the reasoning process by which a general conclusion is inferred from a particular premiss or premisses. There is more than one kind of generalization, but the one relevant to this fallacy is statistical generalization. In a statistical generalization, one infers something about a whole group based on a part of that group. In statistics, the group that we're interested in is called "the population" and the part that we examine is called "the sample". In order for such an inference to be cogent, the sample must be representative of the whole population. However, one way in which a sample can fail to be representative is for it to be too small. A "hasty" generalization is too quick, that is, it jumps to a conclusion before acquiring sufficient evidence to justify it.

Exposure:


Analysis of the Example: The letter writer criticizes the writer of an article for talking with her 58-year-old mother about a nursing home. She makes a generalization that in "this era, people are living to a healthy and ripe old age". This may be true, at least in comparison to times past, but her only evidence is the example of her 85-year-old mother. Moreover, the letter writer's own description of her mother is of an unusually healthy and active woman for her age. Even if her mother were more representative of women her age, she is just one person. People are too variable in health and the effects of age for a generalization from a sample of one to be warranted.

Sources:

Resource:

Douglas Walton, "Rethinking the Fallacy of Hasty Generalization". A technical scholarly paper. At the beginning, Walton discusses the interpretation of hasty generalization given in this entry, but proceeds in the rest of the article to argue for a different interpretation. These are not rival fallacies―though they may vie for the name "hasty generalization"―because each involves a distinct type of generalization.

Acknowledgment: Thanks to Harry Doble for pointing out a broken link to the Resource.