diff --git a/GPy/likelihoods/Gaussian.py b/GPy/likelihoods/Gaussian.py
index 9a992ac1..ed48caf0 100644
--- a/GPy/likelihoods/Gaussian.py
+++ b/GPy/likelihoods/Gaussian.py
@@ -5,20 +5,24 @@ class Gaussian(likelihood):
     def __init__(self,data,variance=1.,normalize=False):
         self.is_heteroscedastic = False
         self.Nparams = 1
-        self.data = data
-        self.N,D = data.shape
         self.Z = 0. # a correction factor which accounts for the approximation made
 
         #normalisation
         if normalize:
             self._mean = data.mean(0)[None,:]
             self._std = data.std(0)[None,:]
-            self.Y = (self.data - self._mean)/self._std
         else:
             self._mean = np.zeros((1,D))
             self._std = np.ones((1,D))
-            self.Y = self.data
 
+        self.set_data(data)
+
+        self._set_params(np.asarray(variance))
+
+    def set_data(self,data):
+        self.data = data
+        self.N,D = data.shape
+        self.Y = (self.data - self._mean)/self._std
         if D > self.N:
             self.YYT = np.dot(self.Y,self.Y.T)
             self.trYYT = np.trace(self.YYT)
@@ -26,9 +30,6 @@ class Gaussian(likelihood):
             self.YYT = None
             self.trYYT = None
 
-        self._set_params(np.asarray(variance))
-
-
     def _get_params(self):
         return np.asarray(self._variance)