Learning Outcomes
- Construct a time series graph
To construct a time series graph, we must look at both pieces of our paired data set. We start with a standard Cartesian coordinate system. The horizontal axis is used to plot the date or time increments, and the vertical axis is used to plot the values of the variable that we are measuring. By doing this, we make each point on the graph correspond to a date and a measured quantity. The points on the graph are typically connected by straight lines in the order in which they occur.
Example
The following data shows the Annual Consumer Price Index, each month, for ten years. Construct a time series graph for the Annual Consumer Price Index data only.
Year | Jan | Feb | Mar | Apr | May | Jun | Jul |
---|---|---|---|---|---|---|---|
2003 | [latex]181.7[/latex] | [latex]183.1[/latex] | [latex]184.2[/latex] | [latex]183.8[/latex] | [latex]183.5[/latex] | [latex]183.7[/latex] | [latex]183.9[/latex] |
2004 | [latex]185.2[/latex] | [latex]186.2[/latex] | [latex]187.4[/latex] | [latex]188.0[/latex] | [latex]189.1[/latex] | [latex]189.7[/latex] | [latex]189.4[/latex] |
2005 | [latex]190.7[/latex] | [latex]191.8[/latex] | [latex]193.3[/latex] | [latex]194.6[/latex] | [latex]194.4[/latex] | [latex]194.5[/latex] | [latex]195.4[/latex] |
2006 | [latex]198.3[/latex] | [latex]198.7[/latex] | [latex]199.8[/latex] | [latex]201.5[/latex] | [latex]202.5[/latex] | [latex]202.9[/latex] | [latex]203.5[/latex] |
2007 | [latex]202.416[/latex] | [latex]203.499[/latex] | [latex]205.352[/latex] | [latex]206.686[/latex] | [latex]207.949[/latex] | [latex]208.352[/latex] | [latex]208.299[/latex] |
2008 | [latex]211.080[/latex] | [latex]211.693[/latex] | [latex]213.528[/latex] | [latex]214.823[/latex] | [latex]216.632[/latex] | [latex]218.815[/latex] | [latex]219.964[/latex] |
2009 | [latex]211.143[/latex] | [latex]212.193[/latex] | [latex]212.709[/latex] | [latex]213.240[/latex] | [latex]213.856[/latex] | [latex]215.693[/latex] | [latex]215.351[/latex] |
2010 | [latex]216.687[/latex] | [latex]216.741[/latex] | [latex]217.631[/latex] | [latex]218.009[/latex] | [latex]218.178[/latex] | [latex]217.965[/latex] | [latex]218.011[/latex] |
2011 | [latex]220.223[/latex] | [latex]221.309[/latex] | [latex]223.467[/latex] | [latex]224.906[/latex] | [latex]225.964[/latex] | [latex]225.722[/latex] | [latex]225.922[/latex] |
2012 | [latex]226.665[/latex] | [latex]227.663[/latex] | [latex]229.392[/latex] | [latex]230.085[/latex] | [latex]229.815[/latex] | [latex]229.478[/latex] | [latex]229.104[/latex] |
Year | Aug | Sep | Oct | Nov | Dec | Annual |
---|---|---|---|---|---|---|
2003 | [latex]184.6[/latex] | [latex]185.2[/latex] | [latex]185.0[/latex] | [latex]184.5[/latex] | [latex]184.3[/latex] | [latex]184.0[/latex] |
2004 | [latex]189.5[/latex] | [latex]189.9[/latex] | [latex]190.9[/latex] | [latex]191.0[/latex] | [latex]190.3[/latex] | [latex]188.9[/latex] |
2005 | [latex]196.4[/latex] | [latex]198.8[/latex] | [latex]199.2[/latex] | [latex]197.6[/latex] | [latex]196.8[/latex] | [latex]195.3[/latex] |
2006 | [latex]203.9[/latex] | [latex]202.9[/latex] | [latex]201.8[/latex] | [latex]201.5[/latex] | [latex]201.8[/latex] | [latex]201.6[/latex] |
2007 | [latex]207.917[/latex] | [latex]208.490[/latex] | [latex]208.936[/latex] | [latex]210.177[/latex] | [latex]210.036[/latex] | [latex]207.342[/latex] |
2008 | [latex]219.086[/latex] | [latex]218.783[/latex] | [latex]216.573[/latex] | [latex]212.425[/latex] | [latex]210.228[/latex] | [latex]215.303[/latex] |
2009 | [latex]215.834[/latex] | [latex]215.969[/latex] | [latex]216.177[/latex] | [latex]216.330[/latex] | [latex]215.949[/latex] | [latex]214.537[/latex] |
2010 | [latex]218.312[/latex] | [latex]218.439[/latex] | [latex]218.711[/latex] | [latex]218.803[/latex] | [latex]219.179[/latex] | [latex]218.056[/latex] |
2011 | [latex]226.545[/latex] | [latex]226.889[/latex] | [latex]226.421[/latex] | [latex]226.230[/latex] | [latex]225.672[/latex] | [latex]224.939[/latex] |
2012 | [latex]230.379[/latex] | [latex]231.407[/latex] | [latex]231.317[/latex] | [latex]230.221[/latex] | [latex]229.601[/latex] | [latex]229.594[/latex] |
Try It
The following table is a portion of a data set from www.worldbank.org. Use the table to construct a time series graph for CO2 emissions for the United States.
CO2 Emissions | |||
---|---|---|---|
Ukraine | United Kingdom | United States | |
2003 | [latex]352,259[/latex] | [latex]540,640[/latex] | [latex]5,681,664[/latex] |
2004 | [latex]343,121[/latex] | [latex]540,409[/latex] | [latex]5,790,761[/latex] |
2005 | [latex]339,029[/latex] | [latex]541,990[/latex] | [latex]5,826,394[/latex] |
2006 | [latex]327,797[/latex] | [latex]542,045[/latex] | [latex]5,737,615[/latex] |
2007 | [latex]328,357[/latex] | [latex]528,631[/latex] | [latex]5,828,697[/latex] |
2008 | [latex]323,657[/latex] | [latex]522,247[/latex] | [latex]5,656,839[/latex] |
2009 | [latex]272,176[/latex] | [latex]474,579[/latex] | [latex]5,299,563[/latex] |
Uses of a Time Series Graph
Time series graphs are important tools in various applications of statistics. When recording values of the same variable over an extended period of time, sometimes it is difficult to discern any trend or pattern. However, once the same data points are displayed graphically, some features jump out. Time series graphs make trends easy to spot.