Year 7 Science · AC9S7I05

Patterns, trends, relationships and anomalies

Use evidence, not isolated values, to describe what the data show.

Plant height after 14 days (cm), three trials:
Low light: 8, 9, 8 · Medium light: 14, 15, 14 · High light: 19, 20, 31
  1. Describe the overall relationship between light category and plant height.
  2. Identify the likely anomaly and explain why it is unusual.
  3. Calculate the mean for the medium-light group.
  4. Calculate the range for the high-light group including the unusual value.
  5. Should 31 cm be deleted immediately? Explain the correct scientific response.
  6. Distinguish a pattern from a trend.
  7. Why is one unusually high point not itself an increasing trend?
  8. Rainfall rises and frog observations also rise. Why does this not automatically prove rainfall caused the increase?
  9. Write a cautious prediction if the observed relationship continues beyond the measured range.
  10. A graph and table appear to disagree. List two checks to perform before deciding which is wrong.
  11. Explain how an average can hide important variation in repeated trials.
  12. Write a high-quality analysis sentence using this structure: variables → direction/form → numerical evidence → anomaly/qualification.

Answers / marking guidance

1–5

1 Plant height generally increases from low to medium to high light in these data. 2 31 cm is far above the other high-light repeats (19 and 20 cm). 3 (14+15+14)/3 = 14.33 cm, about 14.3 cm. 4 31−19 = 12 cm. 5 No: check transcription/units, instrument and method, compare repeats or repeat measurement, then retain/flag or justify exclusion transparently.

6–9

6 Pattern = repeated regularity; trend = overall direction through ordered data. 7 A trend describes overall behaviour across multiple points, not one isolated value. 8 Association does not establish causation; other variables such as temperature, season or sampling effort may influence both. 9 Accept a cautious extrapolation such as “If the relationship continues within similar conditions, greater light may be associated with greater height”; do not claim certainty beyond measured range.

10–12

10 Check transcription/units and that the graph uses the same raw dataset, axes and scale; recalculate processing. 11 Different spreads can share the same mean, and an anomaly can strongly shift a mean. 12 Example: “Plant height generally increased with light category: typical values rose from 8–9 cm in low light to 19–20 cm in high light, although the 31 cm high-light result is anomalous and should be checked before drawing a stronger conclusion.”