In reply to Gerald.

Yes, the geometric mean is sometimes used when the data span several orders of magnitude. It works because the log transformation is a normalizing transformation. By computing the mean of the log-transformed data, you negate some of the influence of the extreme observations.

Some people claim that the geometric mean is robust to outliers, but that statement is not strictly true. There are better choices for robust estimates of a mean. However, the geometric mean is "resistant" to outliers, provided they are not too extreme, for the reason mentioned above.