#set document(title: "18.9 Statistical Literacy", author: "OpenStax")
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== 18.9#h(0.6em)Statistical Literacy


    #notebox("Note", rgb("#8a94a6"), rgb("#556666"), rgb("#f7f8fa"))[
#emph[Prerequisites]


      Benefits, Rank Randomization for Two Conditions, Levels of Measurement #linebreak()  #linebreak()
]


    Cardiac troponins are  markers of  myocardial damage. The levels of troponin in subjects with and without signs of right ventricular strain in the electrocardiogram were compared in the experiment #link("http://www.bmj.com/content/326/7384/312")[described here].  #linebreak() 
                #linebreak() 
             The Wilcoxon rank sum test was used to test for significance. The  troponin concentration in patients with signs of right ventricular strain was higher (median = 0.03 ng/ml) than in patients without right ventricular strain (median \< 0.01 ng/ml), p\<0.001.


    
=== What do you think?


    Why might the authors have used the Wilcoxon test rather than a t test? Do you think the conclusions would have been different? #linebreak()


    Perhaps the distributions were very non-normal. Typically a transformation can be done to make a distribution more normal but that is not always the case. It is almost certain the same conclusion would have been reached, although it would have been described in terms of mean differences instead of median differences.