for example
log(write)= β0 + β1*female = 3.89 + .10*female
Now we can map the parameter estimates to the geometric means for the two groups. The intercept of 3.89 is the log of geometric mean of write when female = 0, i.e., for males. Therefore, the exponentiated value of it is the geometric mean for the male group: exp(3.892) = 49.01. What can we say about the coefficient for female? In the log scale, it is the difference in the expected geometric means of the log of write between the female students and male students. In the original scale of the variable write, it is the ratio of the geometric mean of write for female students over the geometric mean of write for male students, exp(.1032614) = 54.34383/49.01222 = 1.11. In terms of percent change, we can say that switching from male students to female students, we expect to see about 11% increase in the geometric mean of writing scores.
----from
http://www.ats.ucla.edu/stat/mul ... rmed_regression.htm