Evidence-Based Reasoning and Argumentation
From Data to Defensible Claims
An evidence-based argument links a claim to evidence through explicit reasoning, and acknowledges limitations. Strong arguments separate observation from interpretation, quantify uncertainty, and consider alternative explanations. Use inductive reasoning to generalize from patterns and deductive reasoning to apply principles to specific cases; recognize that neither guarantees truth. A counterargument you address strengthens your case more than one you ignore.
Concepts to Know
- Claim–evidence–reasoning structure and warrants connecting them.
- Correlation vs. causation; plausible confounders.
- Statistical vs. practical significance.
- Anecdote vs. systematic evidence.
- Logical fallacies: hasty generalization, false cause, appeal to authority, cherry-picking, slippery slope.
Traps in Questions
- Accepting a causal conclusion from correlational data.
- Overgeneralizing from a small or biased sample.
- Treating a single dramatic example as proof.
- Ignoring base rates or comparison groups when interpreting a result.
- Presenting a claim without stating its limits or rival explanations.
Worked Example / Rule of Thumb
Rule of thumb: for every claim, ask "What evidence supports this, and what else could produce the same pattern?" Example: a student finds students who eat breakfast score higher on a morning quiz and concludes breakfast causes better scores. A stronger argument notes the correlation, then flags confounders (sleep, arrival time, test anxiety) and recommends a design that controls them before asserting causation.