Take the 2-minute tour ×  First of all, let me show you guys the
equation in question.  CFL Equation  In this equation S, V, and
t are known constants. CFL is also known. We have an initial
value for D, and we have no idea what k is.  What I need to do
is find ideal values for both D and k that would minimize the
residuals squared of a calculated CFL and a measured CFL. Using
residuals squared is just a way for me to check if they're the
best possible values, but it's fine if there's another way to go
about this that uses some other method.  The residual squared is
just the absolute value of the difference between the calculated
and measured CFLs, which is then squared. The lower the residual
squared, the better the fit we have. So I need the smallest
possible residual squared resulting from putting both k and D
into the equation. That'll result in a calculated CFL, which I
can then compare to a measured CFL, allowing me to calculate the
residual squared.  My first idea for how to do this, since I'm
not sure