Analysing time series graphs - TSN

Analyse time series graphs using the TSN framework -- identifying the long-term Trend, Seasonality, and Noise present in a dataset, and explaining what each component reveals.

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Te reo Māori terms

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Learning objective overview

Master Teaching Guide coverage for this objective.

Current NZC (2007)
  • S4-1
New NZC (2026)
  • NZC26-P4-STA-DKD-K-Y9-07
  • NZC26-P3-STA-VIS-K-Y7-03

Resources

  • Beta: Skills in Ex 31.03, pg 590

Terminology

  • time series
  • long-term trend
  • seasonality
  • noise

Task goals

  • Recall what T, S, and N stand for in the TSN framework for time series analysis.
  • Identify the long-term trend in a time series as increasing or decreasing (never as \"positive\" or \"negative\").
  • Identify seasonality as a regular, repeating pattern in the data.
  • Identify noise as an unusual or unexpected point that doesn't fit the trend or seasonal pattern.
  • Analyse a described or graphed dataset to identify all three TSN components together.
  • Explain how trend, seasonality, and noise can mask or be mistaken for one another, and justify TSN classifications with reasoning.

Where this fits

What leads into this objective, and where it goes next.

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Analysing time series graphs - TSN

Analysing time series graphs - TSN

Know

A time-series investigation looks at a variable over time.

Statement▸
Year 9 · Statistics · Developing knowledge from data
NZC26-P4-STA-DKD-K-Y9-07

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