diff --git a/pyerrors/fits.py b/pyerrors/fits.py
index 677f6eba..85e28557 100644
--- a/pyerrors/fits.py
+++ b/pyerrors/fits.py
@@ -301,8 +301,7 @@ def total_least_squares(x, y, func, silent=False, **kwargs):
 
     result = []
     for i in range(n_parms):
-        result.append(derived_observable(lambda x, **kwargs: x[0], list(x.ravel()) + list(y), man_grad=list(deriv_x[i]) + list(deriv_y[i])))
-        result[-1]._value = out.beta[i]
+        result.append(derived_observable(lambda my_var, **kwargs: my_var[0] / x.ravel()[0].value * out.beta[i], list(x.ravel()) + list(y), man_grad=list(deriv_x[i]) + list(deriv_y[i])))
 
     output.fit_parameters = result + const_par
 
@@ -419,8 +418,7 @@ def _prior_fit(x, y, func, priors, silent=False, **kwargs):
 
     result = []
     for i in range(n_parms):
-        result.append(derived_observable(lambda x, **kwargs: x[0], list(y) + list(loc_priors), man_grad=list(deriv[i])))
-        result[-1]._value = params[i]
+        result.append(derived_observable(lambda x, **kwargs: x[0] / y[0].value * params[i], list(y) + list(loc_priors), man_grad=list(deriv[i])))
 
     output.fit_parameters = result
     output.chisquare = chisqfunc(np.asarray(params))
@@ -614,8 +612,7 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
 
     result = []
     for i in range(n_parms):
-        result.append(derived_observable(lambda x, **kwargs: x[0], list(y), man_grad=list(deriv[i])))
-        result[-1]._value = fit_result.x[i]
+        result.append(derived_observable(lambda x, **kwargs: x[0] / y[0].value * fit_result.x[i], list(y), man_grad=list(deriv[i])))
 
     output.fit_parameters = result + const_par