title: 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.
authors.affiliation: Pfizer Limited, Bombay.
authors.forename: A S
authors.initials: AS
authors.lastname: Nanivadekar
authors.forename: A R
authors.initials: AR
authors.lastname: Kannappan
mesh_terms: D001172:Arthritis, Rheumatoid / Q000097:blood; D001799:Blood Sedimentation; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D010003:Osteoarthritis / Q000097:blood; D012016:Reference Values