Diane,

The difference is that the standardized regression coefficient is based on converting all of the data points into z scores (or standard scores):

z = (x - mu) / s

which represent the number of standard deviations an individual score is from its mean (as in the normal distribution).

The interpretation of the equation is basically the same, whether it is standardized or unstandardized, however, the with the standardized regression, you can more easily determine the percent contribution of each coefficient (independent variable) in the equation.

Sometimes, when you have several independent variables in a regression model, and they all have widely different measurement scales, it can make the picture a bit more clear by converting everything to standard scores.

Here's a good link:

http://www.csulb.edu/~msaintg/ppa696/696regmx.htm#STANDARDIZED
Hope this helps a bit,

John