Evidence and Reasoning

Year 9 HEAP • Persuasion • Evidence

Evidence does not speak for itself. A number, a quotation or a story becomes evidence only when someone explains what it shows and why it supports the claim. The same fact can be used honestly or misleadingly.

Types of evidence

Type	What it can show	What to check
Statistics	Scale, frequency, change over time or differences between groups.	What is measured, who was counted, when, and whether the sample is representative.
Examples	What a policy or problem looks like in a specific place.	Whether one example is typical or exceptional.
Testimony	Experience, expertise or perspective.	Whether the speaker has relevant knowledge and something to gain.
Documents	Official decisions, rules, budgets or records.	Whether the document is current, complete and being read accurately.
Research	Patterns found across many cases.	Whether the study is relevant to this audience and context.
Observation	What can be seen or counted directly.	Whether the observation was systematic or selective.
Values	What a community believes is fair, safe or worthwhile.	Whether the value is stated openly rather than smuggled in as a fact.

Five tests

Test	Question	Red flag
Relevance	Does this evidence actually bear on the claim?	A fact that is interesting but unrelated.
Accuracy	Is the evidence correct and quoted in context?	A number without a source, or a truncated quotation.
Sufficiency	Is there enough evidence to support the scale of the claim?	One anecdote used to generalise to everyone.
Currency	Is the evidence recent enough for this issue?	Old data presented as current.
Representativeness	Does the sample reflect the people affected?	A survey of one group used to speak for all.

Reasoning patterns

Pattern	How it works	What can go wrong
Causal	X causes Y.	Correlation is treated as causation; another cause is ignored.
Example	This case shows a wider pattern.	The case is untypical or cherry-picked.
Analogy	X is like Y, so what works for Y may work for X.	The differences matter more than the similarities.
Authority	A credible source supports the claim.	The authority is outside their expertise or has a conflict of interest.
Values	The proposal fits what the community believes is fair.	The value is assumed rather than argued, or only one value is considered.

Common fallacies in campaigns

Fallacy	What it looks like	Better move
False dilemma	"Either you support this campaign or you don't care about the issue."	Acknowledge other priorities and explain why this action is worth choosing now.
Slippery slope	"If we allow this, everything will collapse."	Show the actual mechanism and the safeguards.
Ad hominem	Attacking the person instead of the argument.	Address the claim and its evidence.
Straw man	Misrepresenting an opponent's view to make it easier to refute.	State the strongest version of the objection.
Appeal to fear	Exaggerating a threat to force action.	State the risk accurately and pair it with a feasible response.
Cherry-picking	Using only the data that supports the campaign.	Include the strongest contrary evidence and explain it.
Bandwagon	"Everyone is doing it."	Explain why the action is worth doing, not just popular.
False cause	Assuming one event caused another because it happened first.	Look for alternative explanations and evidence of mechanism.

Evidence log

Claim it supports	Source and date	What it shows	What it cannot show	How I will use it

Worked example: a road-safety campaign

A campaign argues for a lower speed limit outside a school. The strongest evidence is not a single dramatic story; it is a combination of crash data, traffic counts and observations of driver behaviour at pick-up time. The campaign should also acknowledge that a lower limit will not work without enforcement, road design and driver education. That qualifier makes the argument more credible, not weaker.

Common errors

Number without meaning. A statistic is quoted but not interpreted.
One story, one conclusion. A single experience is treated as proof of a pattern.
Ignoring the counter-evidence. The campaign only cites sources that agree with it.
False precision. A made-up percentage or an exact prediction that cannot be supported.
Appeal to authority. A famous person is treated as an expert on everything.

Use the research and source evaluation page to check where the evidence comes from.