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+  <clipPath id="pa6e23b6270">
    <rect x="68.87" y="10.8" width="206.6725" height="64.12"/>
   </clipPath>
-  <clipPath id="p0537addfae">
+  <clipPath id="p6e2efc8552">
    <rect x="289.8425" y="91.84" width="59.3575" height="226.2"/>
   </clipPath>
  </defs>
diff --git a/docs/statlab_kappa.rst b/docs/statlab_kappa.rst
index eeb2d01a..9ba770f4 100644
--- a/docs/statlab_kappa.rst
+++ b/docs/statlab_kappa.rst
@@ -410,7 +410,7 @@ Output:
 
 .. testoutput::
 
-    Cohen's kappa (mtbp3.statlab): -0.07283167119975827
+    Cohen's kappa (mtbp3.statlab): 0.06864954183566166
     Number of raters per sample: 2.0
     Number of rating categories: 3
     Number of sample: 100
diff --git a/mtbp3/statlab/kappa.py b/mtbp3/statlab/kappa.py
index 371b7b61..0a771640 100644
--- a/mtbp3/statlab/kappa.py
+++ b/mtbp3/statlab/kappa.py
@@ -288,13 +288,13 @@ def create_bubble_plot(self, out_path="", axis_label=[], max_size_ratio=0, hist=
                     data=df0, x="r1", y="r2", kind="scatter", 
                     height=5, ratio=3, marginal_ticks=True, 
                     marginal_kws={"hue": df0['agree'], "multiple": "stack", "weights": sizes, "shrink":.5, "legend": False}, 
-                    joint_kws={"hue": df0['agree'], "size": sizes, "legend": False, "sizes":(min(sizes), max(sizes)*max_size_ratio)}
+                    joint_kws={"hue": df0['agree'], "size": sizes, "legend": False, "sizes":(min(sizes)*max_size_ratio, max(sizes)*max_size_ratio)}
                     ) 
                 if reverse_y:
                     tmp1 = plt.ylim()
                     plt.ylim(tmp1[1], tmp1[0])
             else:
-                sns.scatterplot(data=df0, x="r1", y="r2", size="sizes", sizes=(min(sizes), max(sizes)*max_size_ratio), legend=False)
+                sns.scatterplot(data=df0, x="r1", y="r2", size="sizes", sizes=(min(sizes)*max_size_ratio, max(sizes)*max_size_ratio), legend=False)
                 tmp1 = plt.xlim()
                 tmp1d = ((tmp1[1] - tmp1[0])/n_categories)
                 plt.xlim(tmp1[0] - tmp1d, tmp1[1] + tmp1d)