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.

Building approvals

The table below shows the number of building permits approved for new dwellings in ACT, Australia each year from 1984 to 2013.

Number of approvals for new dwellings
1984
1985
1965
1987
1988
1989
1990
1991
3082
4325
3036
2089
3024
2482
2466
2653
1992
1993
1994
1995
1996
1997
1998
1999
4538
3957
3733
2374
1979
1628
1742
2117
2000
2001
2002
2003
2004
2005
2006
2007
2074
2343
2866
2591
2844
1986
2132
2277
2008
2009
2010
2011
2012
2013
2635
3634
5455
5510
3794
4800

Although it is possible to see some patterns in this table, the trends are clearer in a time series plot.

Click on points to read off the exact number of approvals in any year.

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

It would be interesting to try to associate the peaks and dips in this time series plot with government administrations and economic events! A building contractor might also hope to predict the demand for new buildings in the future from the trend in recent years.