Kim RoenfeldtGeometric means are a robust and precise way to visualize the central tendency of a data set, particularly when examining skewed data or comparing ratios. Measures of central tendency are predominantly presented as arithmetic means or medians that are relatively simple to calculate and interpret, but may be inaccurate in representing data that are not strictly normal. Geometric means represent the best of both worlds, providing estimates that take into account all the observations in a data set without being influenced by the extremes. They can be applied by SAS programmers working in multiple industries including business, finance, health care, and research. Examples are varied and include examining compounded interest rates or returns on investments, assessing population changes in longitudinal data, or investigating lognormal data such lab assay results, biological concentrations, or decay rates.  Fortunately, there are multiple methods in SAS that can be used to calculate geometric means including the GEOMEAN() function, the geomean keyword in PROC SURVEYMEANS, as well as manual data manipulations such as log transformation combined with PROC MEANS and exponentiation. This paper will explain the utility of geometric means and provide examples for using SAS to calculate geometric means and their measures of variability for your data.