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Keywords:

  • confidence intervals;
  • data types;
  • effect size;
  • odds ratio;
  • P-values;
  • risk ratio;
  • statistics

Key content

  • A few key principles are introduced that need to be understood before inferential statistical procedures can be applied or interpreted.
  • The ‘inputs’ and ‘outputs’ of a generalised univariate statistical analysis are outlined.
  • The greater value of interval estimation, over significance testing, is emphasised.
  • Distinction is made between statistical significance and clinical importance.
  • Examples of commonly used two-group analyses for independent samples are explained and discussed.

Learning objectives

  • To understand the principles underpinning the application of inferential statistical methods.
  • To be able to interpret and apply a few commonly used statistical procedures.
  • To identify when parametric and non-parametric tests are suitable to apply to data.
  • To distinguish between an odds ratio and a risk ratio.

Ethical issues

  • A study that is statistically flawed is ethically flawed.