Time series data

Many data sets contain measurements that are made sequentially at regular intervals. These data are called time series.

Time series data are widely analysed in the business world — accurate forecasting of exchange rates, share prices, demand for products and other business variables can have a major effect on profitability.

The importance of plotting

It is often difficult to get useful information from time series if they are presented in tabular form. As with other data structures, the information in a time series is most easily understood from a graphical display.

A time series plot is a type of dot plot in which the values are displayed as crosses against a vertical axis. The horizontal axis spreads out the crosses in time order. (It can also be thought of as a scatterplot in which the 'explanatory' variable is time.) The successive crosses are often joined by lines.

Temperatures in Wollongong

The table below shows the maximum daily temperatures (in degrees Celsius) at Wollongong, Australia during one month.

Maximum daily temperatures in July 1994
July 1
July 2
July 3
July 4
July 5
July 6
July 7
July 8
July 9
July 10
July 11
14.9
16.9
18.2
22.3
21.9
21.5
22.2
18.0
20.0
18.2
19.8
July 12
July 13
July 14
July 15
July 16
July 17
July 18
July 19
July 20
July 21
 
15.6
16.7
17.0
18.6
17.2
14.4
17.4
17.3
18.1
17.4
 
July 22
July 23
July 24
July 25
July 26
July 27
July 28
July 29
July 30
July 31
 
13.1
13.6
15.0
18.3
16.3
15.8
18.3
20.8
20.0
13.8
 

Although it is possible to see some of the variation in temperatures during the month in this table, the trends are clearer in a time series plot.

Click on points to read off exact temperatures.

Use the checkbox Join crosses to join successive crosses. This makes the movement of the series over time stand out better.

There was a sharp increase in temperature at the beginning of the month, followed by a gradual cooling.