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Figure 1. The raw data from the questionnaires were centered at 0, and plotted againstquestion index (the depth of the question in the questionnaire). Narrowed sectionscorrespond to true/false or 1/0 responses, and the broader areas to questions with a 0-7response scale.However, no easily-discernable patterns are visible in Figure 1. The variation in response fromquestion to question is much greater than any general patterns that might distinguish the fourcases. An alternative representation of the data plots the centered partial sum process againstquestion index,ni.e. S(n)=∑( X i− X ) ),i=1– a technique frequently used in statistical quality control to detect out-of-control manufacturingprocesses. If there is a general positive bias for one case versus another, we should see a gradualseparation of the data points in the graph of S(n) against n. This is shown in Figure 2. That graphapparently shows that the forestry case study (R) separates from the other three, and that theGMO case (G) is somewhat distinct from the pesticide (P) and fisheries (F) cases. Similargraphs can be computed for each of the 5 parts of the questionnaire separately to highlight thedistinct patterns within each of those parts. These are provided in Figures 3 through 7. The Part Igraph is inconclusive. One can see that the forestry case lies above all the others for Parts II, IIIand IV. The pesticide case lies below or close to the bottom of the graphs for Parts II through V.Generally, the fisheries case is frequently a moderate one in the graphs. Of course, one must stillquestion whether the differences are due to the cases or the raters, and these observations arepurely tentative.André Dabrowski – Commentary and Analysis of Research Questionnaires E-11Exploratory Data Analysis of the Institutional Questionnaire