Chapter 9 Flashcards
An introduction to Inductive Arguments
Q: What is inductive reasoning?
A: Reasoning in which we extrapolate from experience to further experience
Q: What are inductive arguments?
A: Arguments in which the premises and the conclusion are empirical- Having to do with observation and experience- and in which the inference to the conclusion is based on an assumption that observed regularities will persist.
Q: What is an inductive generalization?
A: Inductive argument in which the premises describe a number of cases and a generalization is made, so that in the conclusion there is a claim that some or all further cases will have the same property or properties as the cases cited in the premises.
Q: What is retrodiction?
A: Argument that something has happened, or probably happened, in the past, based on evidence about what is happening in the present.
Q: What is a sample?
A: A subset of cases chosen from an identified population and examined as the basis for an inductive generalization. In an inductive generalization, the cases in the sample are assumed to be representative of a broader group of cases. For example, if we reach a conclusion about U.S political opinion by a telephone survey of 1,000 people, these 1,000 people are taken as a sample of the broader adult population in the United States.
Q: What is the Target population?
A: All of the cases within the scope of the conclusion of an inductive generalization. The population is the broader group we are reasoning about, on the basis of our evidence concerning the sample. For example, if someone does a television survey of 1,000 adults in Britain to reach the conclusion about public opinion in Britain on a certain question, the target population is adults in Britain.
Q: What is a random sample?
A: A sample in which every member of the population has an equal chance of being included. Selecting a sample randomly is, strictly speaking necessary for the application of mathematical statistics to the data; however, truly random samples are very difficult to obtain.
Q: what is a biased sample?
A: A sample that demonstrably and obviously misrepresents the population. Such as a sample is unrepresentative because its terms are not typical of the population, and in ways in which they fail to be typical will affect the reliability of the conclusion. For example, if someone were to question people making purchases at a liquor store in attempt to find out what percentage of the adult population consumes more than one alcoholic drink a day, he or she would have a biased sample.
Q: What is representativeness?
A: A sample, S, is perfectly representative of a population, P, with respect to a characteristic, x, if the percentage of S that has X is exactly equal to the of P that has X. We are rarely in a position to know that a sample is representative in this strict sense. (If we were, we would not need the sample; this point is often called the paradox of sampling.) We try to make samples representative by choosing them in such a way that the variety in the sample will reflect variety in population.
Q: What is a Stratified sample?
A: A sample selected in such a way that significant characteristics within the population are (approximately) proportionately represented within it.
Q: What is Statistical syllogism?
A: Argument in which a statistical generalization is applied to an individual or subgroup. Example: 95 percent of Danes are Protestant; Hans is a Dane; so probably Hans is a Protestant.
Q: What is pseudo precision?
A: Claim that appears to be precise due to the use of numbers, but which cannot be precise due to the impossibility of obtaining knowledge with this level of exactness. Often pseudo precision occurs in contexts where an operational definition is faulty.
Q: What does operationalized mean?
A: Defined in measurable terms for the purposes of a study. Compare this notion with that of operational definition, as explained in chapter 3.
Q: What is a hasty inductive generalization?
A: Inductive generalization in which the evidence in the premises is too slight to support the conclusion, usually because the sample is so small that it is extremely unlikely to be representative. The G condition of argument cogency is not satisfied in such a case.
Q: What is an anecdotal argument?
A: Argument in which the premises describe only a single episode, or a few episodes, typically from within the personal experience of the arguer. Such evidence is too slight to be the basis for a cogent inductive generalization. The G condition of argument cogency is not satisfied when evidence is purely anecdotal.
