Introduction to Time Series

A time series is a set of observations obtained by measuring a single variable regularly over a period of time. In a series of inventory data, for example, the observations might represent daily inventory levels for several months. A series showing the market share of a product might consist of weekly market share taken over a few years. A series of total sales figures might consist of one observation per month for many years. What each of these examples has in common is that some variable was observed at regular, known intervals over a certain length of time. Thus, the form of the data for a typical time series is a single sequence or list of observations representing measurements taken at regular intervals.

Table 1. Daily inventory time series
Time Week Day Inventory level
t1 1 Monday 160
t2 1 Tuesday 135
t3 1 Wednesday 129
t4 1 Thursday 122
t5 1 Friday 108
t6 2 Monday 150
    ...  
t60 12 Friday 120

One of the most important reasons for doing time series analysis is to try to forecast future values of the series. A model of the series that explained the past values may also predict whether and how much the next few values will increase or decrease. The ability to make such predictions successfully is obviously important to any business or scientific field.