Biostatistics and epidemiology
Standard deviation, standard error and confidence intervals
Why the standard error shrinks with sample size, how to build a 95% confidence interval for a mean, a proportion and a difference, and how to read intervals against no effect and clinical relevance.
Tier 1Medical sciences concept
Written with AI assistance and fact-checked against the sources below. For exam study, not clinical decisions. How notes are made
At a glance
- SD describes how much individual patients vary. SE describes how precisely a sample estimate pins down the population value: SE = SD / √n.
- A 95% confidence interval is the estimate ± 1.96 SE. It shows the range of true effects compatible with the data.
- Read every interval twice: does it cross the line of no effect (0 for differences, 1 for ratios), and does it exclude a clinically important effect?
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Sources
- Statistics notes: Standard deviations and standard errorsBMJ (Altman and Bland, 2005;331:903), 2005
- Statistics notes: Absence of evidence is not evidence of absenceBMJ (Altman and Bland, 1995;311:485), 1995
- Practical Statistics for Medical ResearchChapman and Hall (Altman, 1991), 1991
- Users' Guides to the Medical Literature: A Manual for Evidence-Based Clinical Practice (3rd ed.)JAMA Evidence / McGraw-Hill (Guyatt et al., 2015), 2015
- Last updated
- 14 November 2026
What changed
- 14 November 2026 Personal emails, About story and Australian-style copy