Teaching hypothesis tests--time for significant change?
Confusion in the teaching of statistical inference dates back to the conflict of Fisher's P-values and significance tests with the Neyman-Pearson hypothesis testing approach. To avoid the well-known pitfalls arising from over-reliance on significance tests and the division of results into 'significant' or 'not significant', many medical journals now insist that presentation of statistical analyses includes confidence intervals as well as or instead of P-values. The confusion over how to report statistical analyses which is evident in the recent medical literature is matched by divergent teaching of hypothesis tests between the 16 U.K. medical schools represented at the April 2000 Burwalls meeting. Suggested guidelines for the teaching of statistical inference to medical students are presented, and possible future developments are discussed.
Sterne
Jonathan A C
JA
Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS8 2PR, UK. jonathan.sterne@bristol.ac.uk
D016001:Confidence Intervals; D003661:Decision Support Techniques; D004504:Education, Medical, Undergraduate / Q000379:methods*; D017408:Guidelines as Topic; D006801:Humans; D012106:Research / Q000706:statistics & numerical data; D013223:Statistics as Topic / Q000193:education*; D013663:Teaching / Q000379:methods*; D006113:United Kingdom