diff --git a/CCREClass.m b/CCREClass.m
index 550694c..a0c6989 100644
--- a/CCREClass.m
+++ b/CCREClass.m
@@ -58,7 +58,7 @@ classdef CCREClass<CREClass
             if isempty(obj.DataRef);return;end %if no refdata given, return;
             %calculate histogram for RefData
             EVarEpsDataGivenRef=0; %clear previous calculations
-            [pDataRef,E]=histcounts(obj.DataRef(:),obj.nBinRef,'Normalization','pdf');
+            [pDataRef,E]=histcounts(obj.DataRef(:),obj.nBinRef,'Normalization','probability');
             [JointHist,E1,E2]=histcounts2(obj.Data(:),obj.DataRef(:),[obj.nBin,obj.nBinRef],'Normalization','probability');
             for k=1:numel(pDataRef) %loop over the bins in pDataRef NB: must be equal to the bins in JointHist for the Ref
                 if pDataRef(k)==0;continue;end% if no data at this line go to the next
diff --git a/TestCREClass.m b/TestCREClass.m
index 24e50c8..8fcdf23 100644
--- a/TestCREClass.m
+++ b/TestCREClass.m
@@ -22,14 +22,25 @@ S.Calc;
 S
 %% Test CCRE class
 figure(1);clf;hold on
-A=randn(10);
-B=randn(10);
+figure(2);clf;
+figure(3);clf;hold on;
+A=randn(100);
+B=A;
+B(:)=A(randperm(numel(A)))
 for k=-1:0.1:1
     CS=CCREClass;
-    CS.Data=(1-abs(k))*A+k*B;
-    CS.nBin=100;
+    CS.Data=1*(1-abs(k))*A+k*B;
+    CS.nBin=50;
     CS.DataRef=B;
-    CS.nBinRef=50;
+    CS.nBinRef=500;
     CS.Calc;
+    figure(1);
     plot(k,CS.CCRE,'o')
-end
\ No newline at end of file
+    plot(k,CS.CRE,'x');
+    figure(2);
+    scatter(CS.DataRef(:),CS.Data(:));
+    figure(3);
+    plot(k,CS.CCRE./CS.CRE,'d');
+    pause(0.01)
+end
+CS
\ No newline at end of file