f[x_] := (a/(1 + ((((x-c)/b))^2)))

??NonlinearModelFit

a=2.2
b = 1.5
c = 0.6
data = Table[{i, f[i] + RandomReal[{-0.3, 0.3}]}, {i, -2.0, 2.0, 0.1}]

ListPlot[data]

fit = NonlinearModelFit[data, (d/(1 + ((((x-g)/e))^2))), {d, e, g}, x]

d
g
e

Show[ListPlot[data], Plot[fit[x], {x, -2, 2}]]

Normal[fit]

fit["ParameterTable"]

Export["~/Desktop/LorentzianData.txt", data, "Table"]

fit["BestFit"]

Needs["ErrorBarPlots`"]

res = Table[{{data[[i, 1]], data[[i, 2]] - fit[data[[i, 1]]]}, ErrorBar[0.3]}, {i, 1, Length[data]}]

ErrorListPlot[res, PlotRange->{-1, 1}]