Statistics for clinicians. 5. Interval data (I).

Abstract

Interval data may be discrete or continuous. They are usually summarized by the average (arithmetic mean). Sometimes, for example when the possible values in a series change by a constant multiple, we need to use the geometric mean. To obtain the overall or mean percentage of a series of percentage values, we need to calculate their weighted mean. The variability of observations in a sample is measured by the standard deviation, and the variability of sample means is measured by the standard error of mean. Confidence interval is a range which contains the population mean with a known probability. It is obtained by deducting from the sample mean, and adding to it, "t" times the SEM, the value of "t" depending on the desired confidence level (1-P) and the sample size (N). The significance of difference between the mean of two sets of unpaired interval data (MA-MB) is tested by Student's t-test. If the data are paired, the significance of the mean difference (MD) is tested by paired t-test. Ordinal data, ie, grades and ranks, may be analyzed by means of the t-test which is more sensitive and allows more refined analyses if needed.