AC9S10I05: Analyse Patterns and Relationships in Evidence

Analysis explains patterns, relationships and anomalies by comparing data sources and scientific models.

By the end of this lesson, you should be able to:

• Comparable data can reveal converging patterns or conflicts.
• Anomalies and uncertainty affect interpretation.
• Explanations connect data patterns to scientific mechanisms or models.

Students should read graphs and tables, distinguish correlation from causation, calculate simple summary statistics and recognise an anomalous value.

Learning sequence: Describe each data set → Align variables and scales → Find convergence or conflict → Explain with a model

Core teaching

• Comparable data can reveal converging patterns or conflicts.
• Anomalies and uncertainty affect interpretation.
• Explanations connect data patterns to scientific mechanisms or models.

Key vocabulary and ideas

• source A
• source B
• shared pattern
• anomaly
• model-based explanation

• Different sources can be averaged immediately: Check units, definitions, sampling and comparability first.
• An anomaly invalidates the whole data set: Test its cause and influence on the relationship.

Keep the Year 10 boundary: Do not combine incompatible data without transformation or caveat. Do not infer cause from pattern alone without design or mechanism.

1. Triangulate three evolution or climate evidence cards.
2. Build one conclusion and one uncertainty statement.

Work through the sequence Describe each data set → Align variables and scales → Find convergence or conflict → Explain with a model, explaining the evidence or mechanism at each step before moving on.

1. Distinguish a pattern, a trend, a relationship and an anomaly using a short example for each.
2. A scatter plot shows a positive association. Explain why this does not by itself establish causation.
3. Identify one plausible measurement cause and one genuine scientific cause of an anomalous data point.
4. Explain when repeating a measurement is preferable to immediately excluding an anomalous value.

A dataset has an overall trend but one clear anomaly. Explain three possible responses: keep it, repeat the measurement, or exclude it, and state what evidence would justify each decision.

Reasoning standard: state the claim, use relevant evidence or a scientific mechanism, and explain why the evidence supports the conclusion without overclaiming.

What is the central idea?

Analysis explains patterns, relationships and anomalies by comparing data sources and scientific models.

What should a strong response do?

Use the sequence Describe each data set → Align variables and scales → Find convergence or conflict → Explain with a model. Connect the evidence, mechanism or data to the claim.

What common trap should I avoid?

Different sources can be averaged immediately: Check units, definitions, sampling and comparability first.

1. Analyse a dataset with a clear overall trend and one anomaly. Describe the trend, quantify it where possible, investigate the anomaly and state a justified conclusion.
2. Two datasets show similar averages but different spread. Explain how that difference could change the scientific interpretation.
3. A media claim says one variable causes another because the two rise together. Evaluate the claim using the distinction between association, mechanism and controlled evidence.

Review hint: Use precise scientific vocabulary, show the relevant mechanism or evidence, and state any limitation or uncertainty when the evidence does not justify a stronger claim.

• I can explain and apply: Comparable data can reveal converging patterns or conflicts.
• I can explain and apply: Anomalies and uncertainty affect interpretation.
• I can explain and apply: Explanations connect data patterns to scientific mechanisms or models.

Exit ticket: Explain the core idea in 3–5 sentences and apply it to one new example without copying the worked model.

Australian Curriculum v9.0 — AC9S10I05: analyse and connect a variety of data and information to identify and explain patterns, trends, relationships and anomalies

Victoria — VC2S10I05, Levels 9–10: Levels 9–10 analysis of patterns, trends, relationships and anomalies in data and information. Victorian Science is banded across Levels 9 and 10, so the VC2S10 code identifies the band rather than a single school year.

NSW: Stage 5 Working scientifically — analyses data to identify trends, patterns and relationships and draws conclusions (SC5-WS-06). Where NSW places the closest concept in another Stage or spreads it across focus areas, this page states that relationship rather than claiming a false one-to-one Year 10 equivalent.

Use these links to move through the learning sequence rather than studying this code in isolation.

• AC9S10I04
• AC9S10I06

• Australian Curriculum v9.0 — Science
• Victorian Curriculum F–10 Version 2.0 — Science
• NSW Science 7–10 Syllabus (2023) — outcomes

Curriculum equivalents for Analyse and connect a variety of data and information to...

Mapped skill: analyse and connect a variety of data and information to identify and explain patterns, trends, relationships and anomalies

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.

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.