# Wednesday, May 11, 2011

Unless a graph provides context, it can fail to give a complete picture of the data it represents. For example, Figure 4a shows the deaths due to traffic accidents in Connecticut in 1955 and 1956.

Figure 4a

These periods were chosen because the state of Connecticut chose to increase the enforcements of speed limits. From the graph, it appears that this increased enforcement saved about 40 lives. However, it’s not possible to make this conclusion because we don’t know what happened prior to 1955 or after 1956. Were traffic deaths in Connecticut already on the increase before the increased enforcement? Did deaths go up again in the years following 1956? The graph during the rest of the decade could have looked like any of the following

Figure 4b

In fact, the graph looked a lot like Figure 4c, which shows traffic deaths on the rise prior to 1955 and continuing to fall after 1956.

Figure 4c

Figure 4d shows even more context for the data.

Figure 4d

In this graph, we see the number of deaths per 100,000 for the entire decade for each state contiguous to Connecticut. While traffic deaths in New York, Massachusetts, and Rhode Island tended to increase or remain steady after 1956, Connecticut’s traffic death rate went down. This context provides strong evidence that Connecticut’s speeding enforcement was effective in its goal of saving lives.

To maximize the meeting supplied by a data graphic, always provide context for that data.

This is an ongoing series discussing the research of Dr. Edward Tufte on Data Visualization.

Wednesday, May 11, 2011 1:10:00 PM (GMT Daylight Time, UTC+01:00)
Wednesday, August 15, 2012 8:48:45 AM (GMT Daylight Time, UTC+01:00)
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