Statistics as a Distillation of Everyday Experience Gerald van Belle, University of Washington, Seattle, WA

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Statistics as a Distillation of Everyday
Experience Gerald van Belle, University of
Washington,Seattle, WA

• Comments byVictor van Daal
• Universitetet i Stavanger, Norge

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Why it is good

• The link of methodology and statistics with
  everyday experience
• We look for consistency in a noisy system we
  look for ways to categorise things, we look for
  causes
• Variation makes it harder to find out whether a
  thing belongs to a certain category or not
• Establishing a link between everyday-life
  reasoning and doing research is important because
  we can use it to train our students
• How to tackle issues of variation and
  causationthe methodology
• How to chose proper tools to examine variation
  and causation the statistics

www.lesesenteret.no
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and its good because

• I recognise a lot in it
• Im biased
• Personally
• The example from a study on Alzheimers
• Professionally
• British Cohort Studies
• Very large data set (17,000 births in week 20 in
  1970) with a follow-up at ages 6, 10, 16, 21, and
  30
• Look for predictors and consequences of
  developmental disorders
• PIRLS (2001) and (2006)
• Comparison of 43 countries on reading
  comprehension performance in 10-year-old
  children, including measures of home, school and
  teacher characteristics

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but

• I dont think its just variation and causation,
  but also measurement, especially because a lot of
  attention is given to IRT (Item Response Theory)
• Or could it be that measurement is in fact
  classification?
• We sort into genres could be extended that we
  use more than one dimension to sort into (with
  again lots of individual variation)
• How do we know that we have a random sample?
• It must be random to avoid bias
• Small samples tend to be biased
• Therefore big samples?

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More variations on variation

• There is no end to controlling variation
• Just by trying to match on very many variables,
  you may unintentionally create differences on an
  unknown variable
• My question would therefore be Why do you wish
  to control variation?
• May be its better to find the sources of
  variation
• Whats there so slippery about representativeness?
  
• Missing values
• When to impute and how to impute?
• When not to impute?

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For the discussion

• Everyday experience may lead us astray in many
  ways
• There are more ingredients to a lethal mix
• How to assess that youre on the same track?
• The great divide
• Anticipate possible problems
• In hindsight how to fix the problems afterwards?
• TheoryExample developmental disorders
• Progressive modularisation, genetic
  constructivism, levels involved
  genetics/biology, cognitive, behavioural
• Research strategy
• Problem solving, responsibilities,