Businesses and economies operate in a dynamic environment. Much of the data that they collect and use are recorded sequentially in time. Examples are
In such time series data, there is often a time-related pattern to the variability. This may be either a trend towards higher or lower values over time or a pattern that repeats regularly. This aspect of overall variability may be explained in terms of the time-ordering of the data.
Time series data are of particular importance in Business Statistics, both to understand what has happened in the past and for forecasting into the future. This chapter describes techniques to analyse patterns in time series and to use these patterns to forecast future values.