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.

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.

Key skills

  • Time series
  • Trend
  • Seasonality
  • Noise
  • TSN

Quick stats

  • 81 total questions
  • 3 difficulty levels
  • Answers included