describe time series plots by identifying features such as trend (long-term direction), seasonality (systematic, calendar-related movements) and irregular fluctuations (unsystematic, short-term fluctuations), and recognise when there are outliers, e.g. one-off unanticipated events
3.2.2.1
smooth time series data by using a simple moving average, including the use of spreadsheets to implement this process
3.2.2.2
calculate seasonal indices by using the average percentage method
3.2.2.3
deseasonalise a time series by using a seasonal index, including the use of spreadsheets to implement this process
3.2.2.4
fit a least-squares line to model long-term trends in time series data, using appropriate technology
