diff --git a/statistics/src/chi_squared_test_draw_graph.py b/statistics/src/chi_squared_test_draw_graph.py
index d39eb86..0a57664 100755
--- a/statistics/src/chi_squared_test_draw_graph.py
+++ b/statistics/src/chi_squared_test_draw_graph.py
@@ -12,9 +12,10 @@ class ChiSquaredTestDrawGraph:
     xlabel: string.
     ylabel: string.
     tight_layout: bool. if execute tight_layout, set True.
+    mode: string. paried or unpaired
     p: float.
     """
-    def draw_graph(self, data, label, title, xlabel, ylabel, tight_layout=False, p=None):
+    def draw_graph(self, data, label, title, xlabel, ylabel, tight_layout=False, mode="paired", p=None):
         """
         fig: make figure instance
         """
@@ -59,11 +60,14 @@ def draw_graph(self, data, label, title, xlabel, ylabel, tight_layout=False, p=N
         ax = plt.gca()
         for i in range(len(y_data1)):
             # x, y, displaying y value, width position, height position (va="top": bottom of (x, y))
-            plt.text(left[i] - 0.02, y_data1[i] / 2.0, (round (y_data1[i] * 100.0)) * 0.01, ha='center', va='top', fontsize=28)
+            plt.text(left[i] - 0.02, y_data1[i] / 2.0, str(str((round (y_data1[i] * 100.0)) * 0.01) + " ("+ str(data[i][0]) +")"), ha='center', va='top', fontsize=28)
 
-        plt.text(left[0] - 0.02, y_data1[i] - (y_data2[0] / 2.0), (round (y_data2[0] * 100.0)) * 0.01, ha='center', va='top', fontsize=28)
-        # avoid overlapping with legend
-        plt.text(left[1] - 0.1, y_data1[1] - (y_data2[1] / 2.0), (round (y_data2[1] * 100.0)) * 0.01, ha='center', va='top', fontsize=28)
+        plt.text(left[0] - 0.02, y_data1[0] + (y_data2[0] / 2.0), str(str((round (y_data2[0] * 100.0)) * 0.01) + " ("+ str(data[0][1]) +")"), ha='center', va='top', fontsize=28)
+        if y_data1[1] + y_data2[1] * 0.5 > 80.0:
+            # avoid overlapping with legend
+            plt.text(left[1] - 0.1, y_data1[1] + (y_data2[1] / 2.0), str(str((round (y_data2[1] * 100.0)) * 0.01) + " ("+ str(data[1][1]) +")"), ha='center', va='top', fontsize=28)
+        else:
+            plt.text(left[1] - 0.02, y_data1[1] + (y_data2[1] / 2.0), str(str((round (y_data2[1] * 100.0)) * 0.01) + " ("+ str(data[1][1]) +")"), ha='center', va='top', fontsize=28)
         """
         add x label in each bar
         """
@@ -71,7 +75,10 @@ def draw_graph(self, data, label, title, xlabel, ylabel, tight_layout=False, p=N
         """
         add title, label
         """
-        new_title = title + "\n(N = " + str(data[0][0] + data[0][1] + data[1][0] + data[1][1]) + " for total (" + str(label[0]) + ": " +  str(data[0][0] + data[0][1]) + ", " + str(label[1]) + ": " + str(data[1][0] + data[1][1]) + "),\n * p < 0.05, ** p < 0.01)"
+        if mode == "unpaired":
+            new_title = title + "\n(N = " + str(data[0][0] + data[0][1] + data[1][0] + data[1][1]) + " for total (" + str(label[0]) + ": " +  str(data[0][0] + data[0][1]) + ", " + str(label[1]) + ": " + str(data[1][0] + data[1][1]) + "),\n * p < 0.05, ** p < 0.01)"
+        elif mode == "paired":
+            new_title = title + "\n(N = " + str(data[0][0] + data[0][1]) + " for each type, * p < 0.05, ** p < 0.01)"
         plt.title(new_title)
         plt.xlabel(xlabel)
         plt.ylabel(ylabel)
diff --git a/statistics/src/sample_chi_squared_test.py b/statistics/src/sample_chi_squared_test.py
index 34e87dc..4d6a02e 100755
--- a/statistics/src/sample_chi_squared_test.py
+++ b/statistics/src/sample_chi_squared_test.py
@@ -14,7 +14,53 @@
         print "python sample_chi_squared_test.py"
     else:
         d = ChiSquaredTestDrawGraph()
-        data = np.array([[1625, 5],[1022, 11]])
-        d.draw_graph(data, ["Condition1", "Condition2"], "test", "x", "y", tight_layout=True)
+        # Q2 children
+        #data = np.array([[43, 28],[19, 52]])
+        # Q2 adults
+        # data = np.array([[8, 12],[11, 9]])
+
+        # enquette
+        # q1. adults (29), children (27)
+        #data = np.array([[20, 9],[18, 9]])
+        # q1. female (30), male (26)
+        #data = np.array([[21, 9],[17, 9]])
+
+        # q2. adults (29), children (27)
+        #data = np.array([[7, 22],[16, 11]])
+        # q2. female (30), male (26)
+        #data = np.array([[15, 15],[8, 18]])
+
+        # q3. adults (29), children (27)
+        #data = np.array([[16, 13],[12, 15]])
+        # q3. female (30), male (26)        
+        #data = np.array([[16, 14],[12, 14]])
+
+        # q4. adults (29), children (27)
+        #data = np.array([[9, 20],[15, 12]])
+        # q4. female (30), male (26)        
+        data = np.array([[13, 17],[11, 15]])
+
+        # q1. adults-children
+        # d.draw_graph(data, ["Adults", "Children"], "The ratio of people who want to use a robot which helps doing household chores", "condition", "percentage", tight_layout=True, mode="unpaired")
+        # q1. female-male
+        # d.draw_graph(data, ["Female", "Male"], "The ratio of people who want to use a robot which helps doing household chores", "condition", "percentage", tight_layout=True, mode="unpaired")
+
+        # q2. adults-children
+        #d.draw_graph(data, ["Adults", "Children"], "The ratio of people who want to use a robot which can be a companion for its user", "condition", "percentage", tight_layout=True, mode="unpaired")
+        # q2. female-male
+        # d.draw_graph(data, ["Female", "Male"], "The ratio of people who want to use a robot which can be a companion for its user", "condition", "percentage", tight_layout=True, mode="unpaired")
+
+        # q3. adults-children
+        # d.draw_graph(data, ["Adults", "Children"], "The ratio of people who want to use a robot which takes care of its user's health", "condition", "percentage", tight_layout=True, mode="unpaired")
+        # q3. female-male
+        # d.draw_graph(data, ["Female", "Male"], "The ratio of people who want to use a robot which takes care of its user's health", "condition", "percentage", tight_layout=True, mode="unpaired")
+
+        # q4. adults-children
+        # d.draw_graph(data, ["Adults", "Children"], "The ratio of people who want to use a robot which its user can raise it", "condition", "percentage", tight_layout=True, mode="unpaired")
+        # q4. female-male
+        # d.draw_graph(data, ["Female", "Male"], "The ratio of people who want to use a robot which its user can raise it", "condition", "percentage", tight_layout=True, mode="unpaired")
+
+        d.draw_graph(data, ["Touch", "Speak"], "The ratio of children who touched or spoke to the robot \n on their own accord", "condition", "percentage", tight_layout=True, mode="paired")
+        # d.draw_graph(data, ["Touch", "Speak"], "The ratio of adults who touched or spoke to the robot \n on their own accord", "condition", "percentage", tight_layout=True, mode="paired")
         # TODO
         # draw table