Quantitative clinical values must always be interpreted not only with the average value in mind but also with the variance of the measure in the reference population.

Ideally, a trained statistician should be involved in the initial design and implementation stages of research studies, in addition to the data analysis stage. A formal methodological review by a trained statistician merits strong consideration in such situations. When developing confidence intervals and other statistical values dependent on variance, researchers must keep in mind that the value of every statistical result is highly dependent on meeting appropriate assumptions. The second concern applies more to research contexts. Thus, while variance around the mean should remain in mind, the clinical context will decide which mean and variance will be used to construct an appropriate reference range. Using this reference range for the newborn population would naturally be inappropriate. However, this only applies to the adult patient population. For instance, a reference range for resting heart rate is between 60 and 100 beats per minute.

When interpreting quantitative clinical measurements using reference ranges (developed using variance), it is of utmost importance to use the correct reference range. Two concerns when considering variance in clinical and research contexts are: (1) using an appropriate reference population (2) ensuring statistical assumptions are met when using variance to develop statistical results.

What does high cost variance mean