Pay Pal Donation
Index of Editorials
Misinformation Statistics Misuse


All Editorials for
2020
2013
2012
2011
2010
2009
2008

Categories
Subcategories

Antarctic Warming
Skepticism [2]

Book
Review [3]

Climate Change
CO2 Emissions [1]

Climate Models
Uncertainty [2]

Climate Science
Climate Cycles [1]
Climate Sensitivity [1]
Holes [1]
Thermal History [1]
Unsolved Problems [1]

Energy Issues
American Power Act [1]
Clean and Sustainable [1]
Nuclear Waste Storage [1]
Renewable Electricity Standard (RES) [1]

Environmentalism
Surrogate Religion [1]

Foreword
Energy Primer for Kids [1]

Geo-Engineering
Applications [2]

Global Climate - International
French Academy [1]

Global Warming
Anthropogenic Global Warming (AGW) [6]
Confusion [1]
Economics [1]
General [2]
Greenhouse Gases [1]
Hockeystick [4]
Ice Cores [1]
Junkscience [9]
Oceans' Role [2]
Skepticism [1]
Sun's Role [2]

Health Issues
Second Hand Smoke [1]

Measurements
Arctic Sea Ice [1]
Atmospheric Temperature Data [2]
Sea Surface Temperature [1]
Surface Data [2]

Misinformation
Statistics Misuse [1]

Modern Empirical Science
v. Medieval Science [1]

NIPCC
China [1]

Nuclear Fuel
Supplies [1]

Organizations
Climate Research Unit (CRU) [1]
International Panel on Climate Change (IPCC) [2]
Nongovernmental International Panel on Climate Change (NIPCC) [1]
UK Met Office [1]
World Meteorological Organization (WMO) [1]

Political Issues
Climate Realism [1]
Climategate [3]
Independent Cross Check of Temperature Data [1]

Report
IPCC Assessment Report [2]
NOAA State of the Climate 2009 [1]
NRC-NAS Advancing the Science of Climate Change [1]

Sea-Level Rise
West Antarctic Ice Sheet (WAIS) [1]
Alarmism [1]

Types of Energy
Nuclear Energy [1]
  • 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.

    View The Week That Was in which this editorial appeared.

    Return to Top of Page


    Free use is granted for non-commercial purposes of all materials on this Website.
    Acknowledgement would be appreciated.
    SEPP is funded through the generous contributions of individuals such as yourself. Pay Pal Donation
    (c) Copyright 2010-2019 Science and Environmental Policy Project