diff --git a/statistics/src/draw_graph.py b/statistics/src/draw_graph.py
index 81f855c..eb152b8 100755
--- a/statistics/src/draw_graph.py
+++ b/statistics/src/draw_graph.py
@@ -35,9 +35,23 @@ def draw_graph(self, data, title, xlabel, ylabel, tight_layout=False, mode="pair
         max_y_data: max y value for scale
         """
         y_data = []
+        tmp=0
         for i in range(len(data.keys())):
-            y_data.append(np.mean(data[(data.keys())[i]]))
-        max_y_data = math.ceil(max(y_data))
+            tmp=0
+            for j in range(len(data[(data.keys())[i]])):
+                print "test: "
+                print data[(data.keys())[i]][j]
+                #print data[((data.keys())[i])[j]]
+                if data[(data.keys())[i]][j] == 1:
+                    tmp += 1
+            print tmp
+            y_data.append(tmp)
+            #y_data.append(np.mean(data[(data.keys())[i]]))
+        tmp_list = []    
+        for i in range(len(data.keys())):
+            tmp_list.append(len((data.keys())[i]))
+        #max_y_data = math.ceil(max(len(data.keys())))
+        max_y_data = math.ceil(max(tmp_list))
         """
         y_error: calculate sample_error as list [err_0, err_1]
         left: list of x value for each bar, now it is just empty
@@ -46,7 +60,10 @@ def draw_graph(self, data, title, xlabel, ylabel, tight_layout=False, mode="pair
         """
         y_error = []
         for i in range(len(data.keys())):
-            y_error.append(np.std(data[(data.keys())[i]], ddof=False))
+            #y_error.append(np.std(data[(data.keys())[i]], ddof=False))
+            y_error.append((len((data.keys())[i]) * np.std(data[(data.keys())[i]], ddof=False)))
+        print "y_error: "
+        print y_error
         left = np.array([])
         """
         left: list of x value (the number of order) for each bar
@@ -106,7 +123,9 @@ def draw_graph(self, data, title, xlabel, ylabel, tight_layout=False, mode="pair
             add p value and mark
             """
             if p < 0.05:
-                input_word = "**" + " (p = " + str(round (p * 1000.0) * 0.001) + " )"
+                #input_word = "**" + " (p = " + str(round (p * 1000.0) * 0.001) + " )"
+                print p
+                input_word = "**" + " (p = " + str(round (p * 100000.0) * 0.00001) + " )"
                 plt.text(1.3, max_y_data * 0.75, input_word)
             elif p < 0.1:
                 input_word = "*" + " (p = " + str(round (p * 1000.0) * 0.001) + " )"
diff --git a/statistics/src/sample_t_test.py b/statistics/src/sample_t_test.py
index 9d2c3db..2d0dd86 100755
--- a/statistics/src/sample_t_test.py
+++ b/statistics/src/sample_t_test.py
@@ -22,7 +22,16 @@
             d.draw_graph(data, "test", "x", "y", tight_layout=True, mode="unpaired-ttest")
 
         elif args[1] == "paired-ttest":
-            # followed this website for sample: http://kogolab.chillout.jp/elearn/hamburger/chap5/sec1.html
-            data = {'HamburgerA':  [90, 75, 75, 75, 80, 65, 75, 80],
-                    'HamburgerB' : [95, 80, 80, 80, 75, 75, 80, 85]}
-            d.draw_graph(data, "test", "x", "y", tight_layout=True)
+            # # followed this website for sample: http://kogolab.chillout.jp/elearn/hamburger/chap5/sec1.html
+            # data = {'HamburgerA':  [90, 75, 75, 75, 80, 65, 75, 80],
+            #         'HamburgerB' : [95, 80, 80, 80, 75, 75, 80, 85]}
+
+            # # children
+            data = {'Talking to the robot': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1],
+                    'Touching the robot':   [0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1]}
+            d.draw_graph(data, "The number of children \nwho spontaneously interacted with the robot", "Action Type", "Number", tight_layout=True)
+
+            # adult
+            # data = {'Talking to the robot': [1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0],
+            #         'Touching the robot':   [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0]}
+            # d.draw_graph(data, "The number of adults \nwho spontaneously interacted with the robot", "Action Type", "Number", tight_layout=True)