title: How do I interpret a confidence interval?
abstract: A 95% confidence interval (CI) of the mean is a range with an upper and lower number calculated from a sample. Because the true population mean is unknown, this range describes possible values that the mean could be. If multiple samples were drawn from the same population and a 95% CI calculated for each sample, we would expect the population mean to be found within 95% of these CIs. CIs are sensitive to variability in the population (spread of values) and sample size. When used to compare the means of two or more treatment groups, a CI shows the magnitude of a difference between groups. This is helpful in understanding both the statistical significance and the clinical significance of a treatment. In this article we describe the basic principles of CIs and their interpretation.
authors.affiliation: Canadian Blood Services, University of Ottawa, Ottawa, Ontario, Canada.|School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: Sheila F
authors.initials: SF
authors.lastname: O'Brien
authors.affiliation: Canadian Blood Services, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: Qi Long
authors.initials: QL
authors.lastname: Yi
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D018401:Sample Size