If I understand your problem, you have n observations where each observation
consists of a y value and one or more x values (x1, x2, ...). the x's and y
are related by a implicit function 0=f(y,x1,x2,...,b1,b2) where b1 and b2
are your parameters. You can solve this problem using solver by creating n
equality constraints (one for each observation) between a hypothetical value
of y, the observed x values, and the parameter values. The objective value
to be minimized is the sum of the squares difference between the observed y
values and the hypothetical y values. The "By changing cells" entry for
solver is the set of hypothetical y cells and the parameter cells. Using
this method, solver will simultaneously solve your equation for y and find
the "best" values for your parameters.

Neal


"ChemEstudent" wrote in message
...
I have an equation I am attempting to fit to some data via 2 variable
constants. However, my equation can't be solved directly. I CAN solve
this equation for my data result variable, but I have to use goalseek
or solver. I want to perform a minimization of a sum of the square of
the differences of my data values and my data result variable. To do
this I would need to imbed a goalseek or solver within the Excel Solver
code. Can anyone help me?