Nonlinear model Fit [closed]

Question

I am trying to fit my data to the function: a + (b*(c/2)^2)/((T - d)^2 + (c/2)^2)

I entered nlm = NonlinearModelFit[data, a + (b*(c/2)^2)/((T - d)^2 + (c/2)^2), {a, b, c, d}, T]

However it returned [0.747-533.437/(260.512+<<1>>^2)]

How can I know the best fit value of each parameter?

data = {{1., -0.58}, {2., -1.507}, {3., -0.932}, {4., -0.3}, {5., \
-1.531}, {6., 0.193}, {7., 
   0.873}, {8., -0.697}, {9., -0.147}, {10., -0.114}, {11., -0.172}, \
{12., -1.847}, {13., 0.636}, {14., -0.846}}/
nlm = NonlinearModelFit[data, 
  a + (b*(c/2)^2)/((T - d)^2 + (c/2)^2), {a, b, c, d}, T]

Answer 1

While, @JimB left a valuable comment, I think that the following is much easier in this case.

data = {{1., -0.58}, {2., -1.507}, {3., -0.932}, {4., -0.3}, {5., \
-1.531}, {6., 0.193}, {7., 
   0.873}, {8., -0.697}, {9., -0.147}, {10., -0.114}, {11., -0.172}, \
{12., -1.847}, {13., 0.636}, {14., -0.846}}
nlm = NonlinearModelFit[data, 
  a + (b*(c/2)^2)/((T - d)^2 + (c/2)^2), {a, b, c, d}, T]

then you do

Normal[nlm]

These are the same values that you would get from the suggestion in the comment.