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22. 11. 2008.
Interpretation of Confidence Interval [Article in Bosnian]
In hypothesis testing, study results expressed through p-values provide information whether to accept or reject a null hypothesis. However, expressed this way they do not provide suffi cient information for a reader to assess the true difference in a measured effect. On the other hand, confi dence interval is informative enough to assess both the difference in a measured effect and its strength and reliability. Confidence interval provides a reader with a span of values that contains the true value with a 95-percent probability and also tells the reader whether the sample is big enough for reliable results.