diff --git a/content/GA_2_8/Analysis_02_solution.ipynb b/content/GA_2_8/Analysis_02_solution.ipynb
index b8e4ec555493a43496d792f548712f700aa2c8fc..09e2df2b5c8fd28781b524b0d472b0075037a364 100644
--- a/content/GA_2_8/Analysis_02_solution.ipynb
+++ b/content/GA_2_8/Analysis_02_solution.ipynb
@@ -496,7 +496,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
@@ -531,9 +531,10 @@
     "print(\"    USING MONTE CARLO SIMULATION    \")\n",
     "print(\"=====================================\")\n",
     "print(f\"Tickets purchased: {t.N()}\")\n",
-    "FD_expected_winnings = np.sum(sampled_probability*sampled_winnings/(Ns+1))\n",
-    "print(f\"Expected winnings: {FD_expected_winnings:9.2e} kUSD ({FD_expected_winnings*1000:5.0f} USD)\")\n",
-    "FD_expected_profit = FD_expected_winnings - t.N()/1000*3\n",
+    "FD_expected_winnings = sampled_probability*sampled_winnings/(Ns+1)\n",
+    "FD_expected_winnings_sum = np.sum(FD_expected_winnings)\n",
+    "print(f\"Expected winnings: {FD_expected_winnings_sum:9.2e} kUSD ({FD_expected_winnings_sum*1000:5.0f} USD)\")\n",
+    "FD_expected_profit = FD_expected_winnings_sum - t.N()/1000*3\n",
     "print(f\"Expected profit:   {FD_expected_profit:9.2e} kUSD ({FD_expected_profit*1000:5.0f} USD)\")\n"
    ]
   },