Week 2: Time series graphics

What you will learn this week

• Different types of plots for time series including time plots, season plots, subseries plots, lag plots and ACF plots.
• The difference between seasonal patterns and cyclic patterns in time series.
• What is “white noise” and how to identify it.

Pre-seminar activities

• Read Chapter 2 of the textbook and watch all embedded videos

Tutorial exercises

NoteTutorial Learning Objectives

1. Apply time series visualisation techniques.
   • Able to create and interpret a range of graphical displays (time plots, seasonal plots, lag plots, and ACF plots) to explore patterns in time series data.
2. Identify and explain key time series features.
   • Analyse visual outputs to detect trend, seasonality, autocorrelation, structural changes, and outliers.
3. Identify white noise behaviour.
   • Use differenced data and ACF plots to determine whether a time series exhibits characteristics of white noise.

• Complete Exercises 6, 7, 11 from Section 2.10 of the book.

Assignments

• IA1 is due on Friday 13 March.
• GA1 is due on Tuesday 24 March.