diff --git a/content/Week_1_4/WS_1_4_Nonlinear_Rain.ipynb b/content/Week_1_4/WS_1_4_Nonlinear_Rain.ipynb
index ab7170dc0b9071417cc9e2459f0a203298a51e3b..a3fd477f00eef1a575eba5d761c192298871a7cc 100644
--- a/content/Week_1_4/WS_1_4_Nonlinear_Rain.ipynb
+++ b/content/Week_1_4/WS_1_4_Nonlinear_Rain.ipynb
@@ -364,7 +364,7 @@
     "\n",
     "Next we will set the stochastic model, and initialize some other variables needed for the <code>while</code>-loop, where the actual Gauss-Newton iteration takes place. Try to see if you can follow the steps above, and fill in the missing code, where you have to compute \n",
     "\n",
-    "- the observed-minus-computed observations <code>Delta_y_i</code> $=\\Delta y_{[i]}$,\n",
+    "- the observed-minus-computed observations <code>Delta_y_i_i</code> $=\\Delta y_{[i]}$,\n",
     "- the estimate <code>Delta_x_hat_i</code>$=\\Delta\\hat{\\mathrm{x}}_{[i]}$,\n",
     "- <code>x_norm</code>$=\\Delta \\hat{\\mathrm{x}}_{[i]}^T \\mathrm{N}_{[i]} \\Delta \\hat{\\mathrm{x}}_{[i]}$\n",
     "\n",
@@ -411,9 +411,9 @@
     "\n",
     "    y_comp_i = compute_y(x_hat_i[:, iteration], times, rain_event)\n",
     "    \n",
-    "    Delta_y = YOUR_CODE_HERE\n",
+    "    Delta_y_i = YOUR_CODE_HERE\n",
     "    \n",
-    "    J_i = jacobian((d_init, a_init, r_init), times, rain_event)\n",
+    "    J_i = jacobian(x_hat_i[:, iteration], times, rain_event)\n",
     "    N_i = J_i.T @ inv_Sigma_Y @ J_i\n",
     "    \n",
     "    Delta_x_hat_i = YOUR_CODE_HERE\n",