MODR Section 9 - Lecture notes 9 PDF

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MODR Section 9-10 Inference: - Cognitive process of drawing a conclusion from evidence - Logical or conceptual process of deriving a statement from one, or more statements - A conclusion reached on the basis of evidence and reasoning - Deriving of one idea from another - Inference can proceed through either “induction” or “deduction” Deductive arguments: - Guarantee the conclusion; accepting the premises logically forces us to accept the conclusion - Logical conditions for good deductive arguments: - Validity - 1. Logical patterns - 2. Topics model - Invalidity - Counterexample method - If the premise are true, the conclusion must also be true - Impossible to have true premise and a false conclusion Inductive arguments: - Can only provide, at best, very strong reasons for the conclusion - Premises provide plausible or probable reasons for the conclusion, but do not absolutely guarantee the conclusion - Are judged in terms of the strengths of the support that they provide for accepting a conclusion, ranging from very weak to very strong 4 most common types of non-deductive arguments 1. Generalizations a. Make general claim about something based on specific evidence about that something b. Process of arriving at a general notion or concept from individual instances i. The result of a process of reasoning from a limited number of cases ii. The conclusion generalizes from a smaller set of instances c. We cannot directly observe a generalization, although we can observe the instance on which it is based and assess the inference from those instances to the generalization d. 2 important elements of a generalization i. Quantities 1. Sample 2. Population 3. sufficient sample size or insufficient sample(sample too small) ii. Qualities 1. Representative sample or unrepresentative sample (qualities should be in same relevant)

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Terms to assess a generalizations 1. Population 2. Sample 3. Qualities: variability of the items in the sample 4. Quantities: frequency of the items in th sample 5. Representativeness of the sample (Error = unrepresentative sample) 6. Size of the sample (Error = insufficient sample) 7. Any possible bias 8. Limitation of scope 9. Overgeneralizations

2. Causal Arguments 3. Appeal to Authority 4. Arguments based on Analogies Mirror test: - Mirror self-recognition test (MSR) - To measure self-awareness Common Characteristics of fallacies of insufficient reasons - Involve presumptions or unwarranted assumptions - Jumps to hasty conclusion - Insufficient sample size - Unrepresentative or biased sample - Over generalization, generalizing beyond the limits of the population - One makes an incorrect generalization based on an isolated, exceptional or inessential case - Violates the “sufficiency” criteria for a good argument by NOT giving ENOUGH reasons in: - Number - Weight - Kind Sweeping generalization fallacy - Occurs when a general rule is applied to a specific case to which the rule is not applicable because of special feature of that case - Example: - Xs are normally Ys - A is an X (where a is abnormal) - Therefore, a is a Y Hasty Generalization Fallacy - Committed when an arguer violates the criteria for a good generalization - Insufficient sample size: too small - Unrepresentative or biased sample - Overgeneralizes: generalizing beyond the limits of the population...