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  • 20-Jun-09 How to Cheat with Statistics
  • SEPP Science Editorial #18-2009
    (in TWTW Jun 20, 2009)

    S. Fred Singer, Chairman and President , Science and Environmental Policy Project (SEPP)

    How to Cheat with Statistics

    Jun 20, 2009

    The standard way is to simply ignore contrary data: for example, the IPCC-AR4 [2007] does not mention or reference climate forcing from changes in solar activity in spite of much published evidence. A more sophisticated method is selectivity: for example, choosing a time interval that will lead to a desired temperature trend [see SEPP Science Editorial #7-08 of Oct 4, 2008]. More difficult to spot is 'selective smoothing' of data that can produce a trend where none exists [see SEPP Science Editorial #8-09 2/28/09].

    We now come to the misuse of averaging, as used in the WH report released this week. Recall that the last National Assessment report (NACC 2000, under Al Gore) used TWO climate models to predict dire futures. Trouble was, their results disagreed violently: in half of the 18 regions they even gave opposite predictions [see NIPCC Summary, figure 16]: For example, the Rio Grande region (New Mexico and West Texas), Upper and Lower Colorado would turn into a desert, acc to one model -while the other model turned them into swamps. So how to fix this strategic error? The new WH Assessment uses an AVERAGE of models instead of showing the results of individual models. It's the old story about the statistician who had one foot in a bucket of ice water and the other in a bucket of boiling water: on the average, he was quite comfortable.

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