Build and annotate the model
Represent evaluating statistically informed arguments and label the important parts, quantities or choices.
Learning goals
Learning goal
Students inspect question wording, sample selection, missing context, graph scale, selected statistics and causal language before deciding how strongly data support a claim.
Success criteria
- I can represent or identify the concept.
- I can explain the underlying relationship.
- I can select an appropriate strategy or feature.
- I can apply it in a new context.
- I can justify and verify the response.
Teaching routine
- Represent
- Reason
- Calculate
- Interpret
- Verify
Curriculum focus: analyse statistically informed arguments presented in traditional and digital media; discuss and critique how data are represented and used to support claims
Key concept
Audit a media statistics claim
Use the visual model first. Ask students to identify the quantities, structure or conditions before calculating or explaining.
1Claim‘9 in 10 prefer Brand A’
2SourceWho conducted and funded it?
3SampleHow many, selected how, from where?
4QuestionWas wording leading?
5DisplayAre scales and categories complete?
6StatisticCount, percentage, mean, mode?
7ConclusionWhat is actually supported?
A numerical statement can be accurate yet misleading if the sample, denominator, comparison or omitted categories are unclear.
Worked examples
Identify common representation tactics
Connect the central relationship to a new context, then verify the conclusion with a second representation, estimate, inverse operation or reasonableness check.
tacticrisktruncated axisexaggerates visual differencesmall voluntary sampleselection biaspercentage without denominatorhides sample sizeaverage without distributionhides spread or extremesassociation phrased as causeoverstates evidence
Critique the argument, not the people. State what additional information would allow a stronger judgement.
Curriculum elaborations explicitly taught
AC9M6ST02: identify statistically informed arguments presented in traditional and digital media; discuss and critique methods, data representations and conclusions
- E1: investigating data representations in the media and discussing what they illustrate and the messages the people who created them might want to convey
- E2: evaluating reports and secondary data relating to the distribution and use of non-renewable resources around the world
- E3: identifying potentially misleading data representations in the media; for example, graphs with broken axes or non-linear scales, graphics not drawn to scale, data not related to the population about which the claims are made and pie charts in which the whole pie does not represent the entire population about which the claims are made
- E4: investigating both traditional and digital media relating to First Nations Australians, identifying and critiquing statistically informed arguments
Use the central and application models above to connect each elaboration to the same underlying concept.
Common misconceptions
Any percentage treated as strong evidenceCheck denominator and sample.
Graph style trusted without valuesRead axes and labels.
Mean considered typical automaticallyInspect distribution and outliers.
Correlation described as causeCausal claims need stronger design and reasoning.
Classroom activities
Compare and reason
Use the application model to compare two cases, explain the relationship and identify a likely error.
Transfer and verify
Apply the idea in an unfamiliar context and use a second method, evidence source or text feature to check it.
Revision Notes and quick mastery check
Check understanding
- Ask who/whom/how many.
- Check denominator.
- Spot truncated axis.
- Question causal language.
- Request missing evidence.
Evidence of mastery
- Represent or identify the concept
- Explain the underlying relationship
- Select an appropriate strategy or feature
- Apply it in a new context
- Justify and verify the response
Decision: continue when students can explain the model, apply it to a new example and justify their check. Otherwise return to the central model and reduce the numerical or representational load.
Curriculum wording and references
Australian Curriculum v9.0
AC9M6ST02: analyse statistically informed arguments presented in traditional and digital media; discuss and critique how data are represented and used to support claims
The Australian Curriculum code and wording are exact. International teachers can use the underlying mathematical concept while matching the lesson to their local grade or year outcomes.
Resources and next steps
Teacher Slides
Project the fixed, branded four-page teaching sequence.
Open Classroom ViewHomework
Use the printable activity for written practice.
Open HomeworkPractice and Test
Use supported Practice first, then the separate Test when ready.
Open PracticeOpen Test
🎥 Optional Video Lesson
The SkillrHub lesson remains the primary learning resource. This optional video reinforces the explanation; you can complete the lesson and practice without watching.
Before you watch:
- Pause after each worked example.
- Try the examples yourself.
- Return to the SkillrHub lesson before continuing.
Recommended: Misleading Line Graphs
Khan Academy — Look critically at graph scales and the impression they create.
As you watch: How can two accurate graphs of the same data appear to tell different stories?
Load video player Loads YouTube in this lesson. See the video notice below.
Try it: Draw the values 48%, 50% and 52% using two vertical scales. Explain which display exaggerates the change and how you would label it fairly.
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Curriculum equivalents: Victoria, NSW and international
Curriculum equivalents for Statistically informed arguments presented in traditional and digital media; discuss...
Mapped skill: identify statistically informed arguments presented in traditional and digital media; discuss and critique methods, data representations and conclusions
These references identify matching or closely related learning. Curriculum sequence, terminology and depth vary, so teachers should use the mapped skill and lesson difficulty to confirm suitability.
| Region | Curriculum framework | Closest level or code |
|---|---|---|
| Australia | Australian Curriculum v9.0 | AC9M6ST02 · Year 6 |
| Victoria | Victorian Curriculum F–10 Version 2.0 — Mathematics | VC2M6ST02 · Level 6 |
| New South Wales | NSW Mathematics K–10 Syllabus (2022) | MA3-DATA-02 · Stage 3 |
| United States (USA) | Common Core State Standards for Mathematics | Grade 6 |
| Canada (Ontario) | Ontario Curriculum — Mathematics | Grade 6 |
| United Kingdom (England) | National Curriculum in England — Mathematics | Year 7, Key Stage 3 |
| India | NCERT / CBSE — Mathematics | Class 6 |
Australian Curriculum v9.0 is the canonical source for this SkillrHub lesson. Victoria and NSW entries name the closest published state codes or outcomes; international entries are planning references rather than claims of identical curricula.
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Topic reference: AC9M6ST02 — Evaluating Statistically Informed Arguments
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