Unit 5 - Non-Deductive Arguments Review

These flashcards cover key concepts related to non-deductive arguments, including definitions, types, evaluation criteria, and common mistakes.

What is a non-deductive argument?

An argument that does not guarantee its conclusion but makes it probable.

What is the goal of non-deductive arguments?

To make the conclusion more likely than not.

What is the difference between deductive and non-deductive arguments?

Deductive = certain; Non-deductive = probable.

What does it mean that non-deductive arguments are a ‘gamble’?

They do not guarantee truth, only likelihood.

How are non-deductive arguments evaluated?

By how likely the conclusion is based on the premises.

What can change the strength of an argument?

New relevant information.

What happens when new premises are added to an argument?

They can strengthen or weaken the argument.

What are successful non-deductive arguments?

Those that make the conclusion likely.

What are unsuccessful non-deductive arguments?

Those that make the conclusion unlikely.

What are the 3 types of non-deductive arguments?

Statistical syllogism, inductive generalization, plausibility.

What is a statistical syllogism?

Reasoning from a group to an individual.

What is the example structure of a statistical syllogism?

Most X are Y, this is X → probably Y.

What must you identify in statistical syllogisms?

Group, member, property, proportion.

What is an inductive generalization?

Reasoning from a sample to a whole group.

What must you identify in inductive generalizations?

Sample, target group, property.

What is a plausibility argument?

An argument based on relevant supporting reasons.

What are the 4 criteria for plausibility?

Truth, relevance, adequacy, missing info.

What is sample size?

Number of observations used.

Why is sample size important?

Too small a sample can lead to a weak argument.

What is a hasty generalization?

Conclusion based on too small a sample.

What is a representative sample?

A sample that accurately reflects the target group.

What is a biased sample?

A sample that does not reflect the target group.

What is random sampling?

Selecting participants randomly to reduce bias.

Why must samples match the population?

To avoid bias in conclusions.

Give an example of a biased sample.

Surveying only students to represent all people.

What happens if a sample is biased?

The argument becomes weak.

What is relevance in arguments?

Premises must relate to the conclusion.

What is adequacy?

Enough support is provided.

What is missing information?

Important facts not considered.

Why be skeptical of popularity in arguments?

Popularity does not equal truth or importance.

What is the biggest mistake in Unit 5?

Confusing probability with certainty.

What should you always ask when evaluating an argument?

How likely is this conclusion?

Can non-deductive arguments be strong?

Yes, even without certainty.

What weakens non-deductive arguments?

Bias, small samples, irrelevant info.

What strengthens non-deductive arguments?

Good data, large representative samples.

What is the key evaluation question for non-deductive arguments?

Does this make the conclusion likely?