title: How do I interpret a p value?
abstract: A p-value is a number between 0 and 1 that is extremely useful in interpreting research results. Using comparison of the means of two samples as an example, a p-value <0.05 suggests that there is enough evidence to presume a real difference between groups from which the samples were drawn (that the "null hypothesis" can be rejected). We say that the difference between the means is statistically significant. However, it isn't iron clad proof and there is still a chance that there is really no difference. Furthermore, a statistically significant difference may not be clinically significant if it is not enough to appreciably affect patient outcomes. We describe the theory behind p-values and some common errors in interpretation.
authors.affiliation: Canadian Blood Services, Ottawa, Ontario, Canada.
authors.forename: Sheila F
authors.initials: SF
authors.lastname: O'Brien
authors.affiliation: Canadian Blood Services, Ottawa, Ontario, Canada.
authors.forename: Lori
authors.initials: L
authors.lastname: Osmond
authors.affiliation: Canadian Blood Services, Ottawa, Ontario, Canada.
authors.forename: Qi-Long
authors.initials: QL
authors.lastname: Yi
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D018401:Sample Size