A.E. Rodriguez & Robert Albright
November 19, 2020
The space shuttle Challenger exploded 73 seconds after lift-off on January 28, 1986.
The cause of the disaster was traced to the failure of an O-ring seal. O-rings were used to isolate the fuel supply from burning gases.
The accident killed the seven crew members.
“We will never forget them, nor the last time we saw them, this morning, as they prepared for their journey and waved goodbye and ‘slipped the surly bonds of earth’ to ‘touch the face of God.'”
The story behind the Challenger disaster is perhaps the most poignant missed opportunity in the history of statistical graphics.
Michael Friendly, Visualizing Categorical Data: Data, Stories, and Pictures (2001)
The Challenger decision was not a failure of quantitative analysis. NASA's real mistake
was to rely on quantitative analysis too much.
David Epstein, Range (2019)
… failures in communication … resulted in a decision to launch 51-L based on incomplete and sometimes misleading information, a conflict between engineering data and management judgments, and a NASA management structure that permitted internal flight safety problems to bypass key Shuttle managers.</q
Rogers Commission Report (1986)
Rogers Commission Report (at 149)
This is the key graph of the O-ring test data that NASA analyzed before launch. Is there any pattern between temperature and the O-ring failure rate? </q
If you were the decision maker for launch and only had this graph, would you have allowed the space shuttle to launch at 31°F, the temperature on the day of the launch?
This linear model represents the implied relationship between distressed O-rings and temperature. Cleary, there is no relationship based on data.
Displaying only the distressed O-rings was an epic-mistake.
[1] "Accuracy= 87 %"
Michael Friendly, 2001
One virtue of a good graphical display is to allow us to see patterns, trends, or other structures which would otherwise be concealed in another form of display. It may be heartbreaking to find out that some important information was there, but the graph maker missed it. The story behind the Challenger Disaster is perhaps the most poignant missed opportunity in the history of statistical graphics. But such graphical failures often provide useful lessons.
Dalal, Nemil, Priceonomics (https://priceonomics.com/)
Dalal, Siddhartha R., Edward B. Fowlkes, and Bruce Hoadley. 1989. “Risk Analysis of the Space Shuttle: Pre-Challenger Prediction of Failure.” Journal of the American Statistical Association 84 (408): 945–57. doi:10.1080/01621459.1989.10478858.
Epstein, David., Range (New York, NY: Riverhead Books, 2019)
Friendly, Michael (2001), Gallery of Data Visualization, Electronic document, http://www.datavis.ca/gallery/
Presidential Commission on the Space Shuttle Challenger Accident. 1986. Report of the Presidential Commission on the Space Shuttle Challenger Accident (Vols. 1 & 2). Washington, DC. http://history.nasa.gov/rogersrep/genindex.htm.