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
4.1.3
smooth time series data by using a simple moving average, including the use of spreadsheets to implement this process
4.1.4
calculate seasonal indices by using the average percentage method
4.1.5
deseasonalise a time series by using a seasonal index, including the use of spreadsheets to implement this process
4.1.6
fit a least-squares line to model long-term trends in time series data
4.1.7
predict from regression lines, making seasonal adjustments for periodic data
