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Table 4 Curricular content

From: Statistics teaching in medical school: Opinions of practising doctors

Basic grounding
"Understanding of basic concepts and data interpretation" (D1:144)
"A basic grounding - population distributions, understanding p-values, confidence intervals, concepts of risk" (D1:15)
"Teaching in the core principles and its application and relevance in current clinical practice" (D1:238)
"They need comprehensive teaching in understanding statistics, epidemiology and critical appraisal as part of EBM. They do not need to learn how to calculate things that can come later" (D1:49)
Specific methods
"Basic probability and statistics up to an understanding of regression (not doing!), basic research methods with understanding of different epidemiological designs ... basic analysis of data using a statistical software package" (D1:194)
"I think all doctors should be able to recognise the basic statistical errors which crop up all the time in research - e.g. using correlation as an indicator of causality. All need to be able to describe relative risks e.g. to know what is the risk of everyday activities (driving etc) so that this can be compared to a risk of treatment or disease usefully to a patient. ..." (D1:260)
"As a minimum undergraduates should know why statistical methods are important, how to describe probability and the basis of simple tests such as t tests. They should know what confidence intervals mean." (D1:118)
"Should be able to understand probability, standard deviation and tests for statistical significance" (D1:449)
"Types of study with relevance to the question; levels of evidence; understanding of meta-analyses; simple stats. e.g. p, CI, parametric/non parametric; common tests; 4 × 4 tables, sensitivity/specificity" (D1:131)
"As now but more on 1) theory of probability and risk, 2) multiple regression and 3) diagnostic inference" (D1:18)