diff --git a/vega/analysis.py b/vega/analysis.py
index 21f5206..efb5c13 100644
--- a/vega/analysis.py
+++ b/vega/analysis.py
@@ -182,7 +182,7 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None):
         self.mc_failed_mask = []
 
         for i in range(num_mocks):
-            print(f'INFO: running Monte Carlo realization {i}')
+            print(f'INFO: Running Monte Carlo realization {i}')
             sys.stdout.flush()
 
             # Create the mocks
@@ -199,7 +199,7 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None):
                 minimizer.minimize()
                 self.mc_failed_mask.append(False)
             except ValueError:
-                print('WARNING: minimizer failed for mock {}'.format(i))
+                print('WARNING: Minimizer failed for mock {}'.format(i))
                 self.mc_failed_mask.append(True)
                 self.mc_chisq.append(np.nan)
                 self.mc_valid_minima.append(False)
@@ -211,12 +211,12 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None):
                     self.mc_bestfits[param] = []
                 self.mc_bestfits[param].append([value, minimizer.errors[param]])
 
-            for param in self.mc_bestfits.keys():
-                self.mc_bestfits[param] = np.array(self.mc_bestfits[param])
-
             self.mc_covariances.append(minimizer.covariance)
             self.mc_chisq.append(minimizer.fmin.fval)
             self.mc_valid_minima.append(minimizer.fmin.is_valid)
             self.mc_valid_hesse.append(not minimizer.fmin.hesse_failed)
 
+        for param in self.mc_bestfits.keys():
+            self.mc_bestfits[param] = np.array(self.mc_bestfits[param])
+
         self.has_monte_carlo = True