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.

Defence Investment in USA

The table below describes the investment in defence in the USA between 1947 and 2006. (Because 1947 dollars were worth less than 2006 dollars, all values have been adjusted for inflation and are reported in '2000 dollars', allowing more meaningful comparisons between the years.)

Real National Defense Gross Investment (2000 $billion)
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
4.9
9.4
13.8
10.8
38.5
55.7
62.4
50.8
41.1
39.3
37.3
39.7
47.3
42.7
47.3
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
48.9
42.3
38.4
33.5
38.7
43.7
38.3
34.0
30.9
19.7
14.7
16.6
20.2
22.5
24.5
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
25.0
24.8
28.4
30.4
33.5
37.7
44.2
50.5
60.7
69.6
76.0
70.3
70.7
72.9
68.7
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
66.1
57.8
53.8
50.9
51.3
45.1
45.6
47.6
48.8
50.8
56.7
61.7
68.0
71.7
76.6

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 exact expenditures.

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

It is interesting to try to associate the peaks and dips in this time series plot with government administrations and international events! A manufacturer in the defence sector might also hope to predict future government expenditure from the trend in recent years.