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Unformatted text preview: Ling 21: Language and Thinking Thinking
Lecture 13 – Inductive Reasoning (Critical Thinking, Chapter 11) Inductive Reasoning Inductive Inductive generalizations Statistical arguments Arguments from analogy Causal arguments Inductive generalizations Inductive In understanding inductive generalizations, you In should . . .
be able to identify the sample population and the be sample population as a whole (i.e. the population that the population generalization is about) in an inductive generalization. understand that a good inductive argument should understand reach a conclusion that is appropriate to the evidence offered in the premises.
• • A more moderate conclusion makes the inference more stronger. stronger. An overstated conclusion makes the inference weaker. Inductive generalizations Inductive In evaluating inductive In generalizations you should ask the generalizations following questions: Are the premises true? Are
• • Is the sample population large enough? Is Is the sample population representative of the Is population as a whole? You should understand that a representative sample You is similar to the population as a whole in all relevant respects. respects. Inductive generalizations Inductive In evaluating generalizations that are In generated through opinion polls, you opinion you should . . . understand that opinion polls operate under the understand same basic standards as other inductive generalizations insofar as the sample must be large enough and representative of the population as a whole;
• • The size of the sample should be large enough to reach an The acceptable margin of error. The sample is best generated randomly (where each The randomly member of the population has an equal chance of being selected) so as to avoid bias. selected) Inductive generalizations Inductive grasp the concepts of level of certainty and margin grasp of error; of recognize the weaknesses in self-selecting recognize samples; samples understand how the tendency of people to respond to understand polls dishonestly, and the tendency of agencies with dishonestly and vested interests to ask slanted questions, can bias a slanted can poll sample; recognize the merits of a double-blind poll for recognize double-blind generating objective results. generating Statistical Arguments Statistical In evaluating statistical arguments, In students should . . . understand the distinction between inductive understand strength and statistical reliability in strength reliability statistical arguments; understand how the specificity of the understand reference class in a statistical argument reference can impact the strength and reliability of the inference. Arguments from Analogy Arguments In evaluating analogical arguments, students In should be able to . . .
discern whether the compared items in an discern analogical argument share a sufficient number of relevant similarities to warrant accepting the relevant conclusion; discern whether the compared items in an discern analogical argument share a sufficient number of relevant dissimilarities to warrant rejecting the relevant conclusion; understand that with increased sample size, understand increased diversity becomes a mark of strength; diversity Arguments from Analogy Arguments understand that with increased sample size, understand increased diversity becomes a mark of strength; diversity gauge the specificity of the conclusion gauge relative to the premises. relative You should understand that the same You standards used to evaluate analogical arguments apply in constructing arguments from analogy. arguments Causal Arguments Causal In evaluating causal arguments, students In should . . . understand that it is easier to show that understand something could not be the cause of some could effect than it is to prove a causal relationship. recognize causal terms such as, produce, is recognize produce responsible for, affects, makes, changes responsible affects makes changes and contributesto; contributesto Causal Arguments Causal recognize whether an argument concerns the cause recognize of a single instance or a general relationship; single general
• note that causal claims about populations usually mean that note some condition or event results in a higher rate of some higher supposed effect in the population, not that every instance of every some event will result in the supposed effect; • note that causal relationships are often complex, so that note even a genuine causal factor may neither be necessary nor sufficient to bring about the effect under consideration; sufficient understand the distorting effect of selective attention understand and memory to evidence supporting a causal and conclusion; understand the unreliability of anecdotal evidence; understand anecdotal Causal Arguments Causal recognize the merit of a controlled experiment in recognize controlled discerning causal relationships;
• be familiar with terminology associated with controlled be experiments: experimental group experimental control group control placebo effect placebo double-blind study distinguish relationships of correlation from distinguish correlation relationships of causation ;
• • distinguish between a positive correlation and a negative distinguish positive negative correlation; understand when a correlation is significant. understand significant Causal Arguments Causal Students should understand the concept of Students probability. To this end, you should be able to probability To recognize and distinguish between . . . • • • • epistemic probability; relative frequency probability; a priori probability. In grasping the concept of a priori priori probability, you should be familiar with the following concepts:
gamblers fallacy; the law of large numbers; the law expected value; relative value; diminishing marginal value. ...
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This note was uploaded on 09/08/2010 for the course LING 21 at San Jose State University .