During next year’s election campaign there will be many claims made on the basis of dubious statistics. RadStats has the chance to raise the standard of the debate by listing the principles for judging if the interpretation of data by candidates and the wider public is valid.
We could produce (five ?) criteria to follow when quoting data, or list frequent errors made in interpreting data. Examples are assuming correlation is causation, treating estimates eg unemployment rates, as actual counts, not being aware of regression to the mean and quoting, without confidence intervals, surveys based on small samples.
These could be summarised in non-technical language iand printed on a postcard for wide distribution, with an eye-catching heading eg “Standards for honest data”.
David Lamb
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