diff --git a/recopytex/dashboard/pages/exams_scores/app.py b/recopytex/dashboard/pages/exams_scores/app.py
index ee6a64d..1144de7 100644
--- a/recopytex/dashboard/pages/exams_scores/app.py
+++ b/recopytex/dashboard/pages/exams_scores/app.py
@@ -55,6 +55,15 @@ layout = html.Div(
                             ],
                             id="final_score_table_container",
                         ),
+                        html.Div(
+                            children=[
+                                dash_table.DataTable(
+                                    id="score_statistics_table",
+                                    columns=[],
+                                )
+                            ],
+                            id="score_statistics_table_container",
+                        ),
                     ],
                     id="analysis",
                 ),
diff --git a/recopytex/dashboard/pages/exams_scores/callbacks.py b/recopytex/dashboard/pages/exams_scores/callbacks.py
index ea0da49..7fe07a5 100644
--- a/recopytex/dashboard/pages/exams_scores/callbacks.py
+++ b/recopytex/dashboard/pages/exams_scores/callbacks.py
@@ -2,7 +2,6 @@
 # encoding: utf-8
 
 from dash.dependencies import Input, Output, State
-import dash
 from dash.exceptions import PreventUpdate
 import dash_table
 import json
@@ -52,7 +51,6 @@ def update_exams_choices(tribe):
     ],
 )
 def update_scores_store(exam):
-    ctx = dash.callback_context
     if not exam:
         return [[], [], [], {}]
     exam = pd.DataFrame.from_dict([json.loads(exam)])
@@ -88,7 +86,26 @@ def update_scores_store(exam):
         Input("scores_table", "data"),
     ],
 )
-def update_scores_store(scores):
+def update_finale_score_table(scores):
     scores_df = pd.DataFrame.from_records(scores)
     # print(scores_df)
     return score_to_final_mark(scores_df)
+
+
+@app.callback(
+    [
+        Output("score_statistics_table", "columns"),
+        Output("score_statistics_table", "data"),
+    ],
+    [
+        Input("final_score_table", "data"),
+    ],
+)
+def update_statictics_table(finale_score):
+    df = pd.DataFrame.from_records(finale_score)
+    statistics = df["mark"].describe().to_frame().T
+    print(statistics)
+    return [
+        [{"id": c, "name": c} for c in statistics.columns],
+        statistics.to_dict("records"),
+    ]