# Fitting plot and data to an equation

If I have the following data:

``data={{2, 66.7635}, {Log/Log, 69.9679}, {Log/Log,    71.54}, {3, 72.2428}, {-2.30103, 54.0023}, {-(Log/Log),    55.1941}, {-(Log/Log), 56.0038}, {-1,    56.9497}, {-(Log/Log), 57.305}, {-(Log[10/3]/Log),    57.7213}, {-(Log/Log), 58.2489}, {-2.30103,    54.0367}, {-(Log/Log), 55.1157}, {-(Log/Log),    56.1704}, {-1, 56.7117}, {-(Log/Log),    57.2506}, {-(Log[10/3]/Log), 57.7097}, {-(Log/Log),    58.1068}} ``

Which looks like this plotted: I have two questions:

1) How can I fit and plot the fit of this data based on the following equation?

: where `Tf'_ref=57.2506` , `q_ref=0.166667` and c1 and c2 are the fitting parameters. Also, notice that `data` is `Tf'` vs `Log q` in the equation.

2) How can I find the values of `c1` and `c2` which are the fitting parameters.

The fitting (orange line) is supposed to look like this (done in excel): EDIT: I tried using `NonLinearFitModel` like this: `Table[{NonlinearModelFit[data, Logqref - ((c1*(data[[i, 2]] - Tfref))/(c2*(data[[i, 2]] - Tfref))), {{c1, 8.6}, {c2, 17.2}}, x]; }, {i, 1, 11}]` but this does not work. The reason I tried this is because `data[[i, 2]]` represents `Tf'` in the equation. Here `Logref=Log10[0.16667]`