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When we reason about quantitative evidence, certain methods for displaying and analyzing data are better than others. Superior methods are more likely to produce truthful, credible, and precise findings. The difference between an excellent analysis and a faulty one can sometimes have momentous consequences.
This chapter examines the statistical and graphical reasoning used in making two life-and-death decisions: how to stop a cholera epidemic in London during September 1854; and whether to launch the space shuttle Challenger on January 28, 1986. By creating statistical graphics that revealed the data, Dr. John Snow was able to discover the cause of the epidemic and bring it to an end. In contrast, by fooling around with displays that obscured the data, those who decided to launch the space shuttle got it wrong, terribly wrong. For both cases, the consequences resulted directly from the quality of methods used in displaying and assessing quantitative evidence.
When we reason about quantitative evidence, certain methods for displaying and analyzing data are better than others. Superior methods are more likely to produce truthful, credible, and precise findings. The difference between an excellent analysis and a faulty one can sometimes have momentous consequences.
This chapter examines the statistical and graphical reasoning used in making two life-and-death decisions: how to stop a cholera epidemic in London during September 1854; and whether to launch the space shuttle Challenger on January 28, 1986. By creating statistical graphics that revealed the data, Dr. John Snow was able to discover the cause of the epidemic and bring it to an end. In contrast, by fooling around with displays that obscured the data, those who decided to launch the space shuttle got it wrong, terribly wrong. For both cases, the consequences resulted directly from the quality of methods used in displaying and assessing quantitative evidence.
When we reason about quantitative evidence, certain methods for displaying and analyzing data are better than others. Superior methods are more likely to produce truthful, credible, and precise findings. The difference between an excellent analysis and a faulty one can sometimes have momentous consequences.
This chapter examines the statistical and graphical reasoning used in making two life-and-death decisions: how to stop a cholera epidemic in London during September 1854; and whether to launch the space shuttle Challenger on January 28, 1986. By creating statistical graphics that revealed the data, Dr. John Snow was able to discover the cause of the epidemic and bring it to an end. In contrast, by fooling around with displays that obscured the data, those who decided to launch the space shuttle got it wrong, terribly wrong. For both cases, the consequences resulted directly from the quality of methods used in displaying and assessing quantitative evidence.