ABSTRACT
The use of statistics in clinical and pharmaceutical settings is extremely
common. Because the data are generally collected under experimental con-
ditions that result in measurements containing a certain amount of error,*
statistical analyses, though not perfect, are the most effective way of making
sense of the data. The situation is often portrayed as
T ¼ tþ e:
Here, the true but unknown value of a measurement, T, consists of a sample measurement, t, and random error or variation, e. Statistical error is considered to be the random variability inherent in any system, not a mistake. For
example, the incubation temperature of bacteria in an incubator might have a
normal random fluctuation of +18C, which is considered a statistical error. A timer might have an inherent fluctuation of +0.01 sec for each minute of actual time. Statistical analysis enables the researcher to account for this
random error.
