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Interactive_Confidence_Interval.ipynb

@@ -271,14 +271,12 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b1e8a58ded314882964e8cc7ecb0a23c",
+       "model_id": "caeda7aedfed4f4b85bac435576d580c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -292,12 +290,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a353af7b01884706bcc7bb4f522ff074",
+       "model_id": "4960f612e5764600a9006fad6cc456ba",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output(outputs=({'output_type': 'stream', 'text': '2 2\\n', 'name': 'stdout'}, {'output_type': 'display_data', …"
+       "Output()"
       ]
      },
      "metadata": {},
@@ -325,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -373,7 +371,7 @@
     "    gs = GridSpec(3, 2, figure=fig)\n",
     "    \n",
     "    ax1 = fig.add_subplot(gs[:, 0])\n",
-    "    boxplot = ax1.boxplot([pred,pgreen],labels = labels, notch = True, sym = '+',patch_artist=True)\n",
+    "    boxplot = ax1.boxplot([pred,pgreen],tick_labels = labels, notch = True, sym = '+',patch_artist=True)\n",
     "    colors = ['red','green']\n",
     "    for patch, color in zip(boxplot['boxes'], colors):\n",
     "        patch.set_facecolor(color)\n",
@@ -514,13 +512,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "90e585d00a8845abb1b53b70ba0b32ca",
+       "model_id": "11af1ac90d5a420aa42298a23d63c07a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -534,12 +532,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4bff03c928e542f9a5e7e891c9d382ac",
+       "model_id": "952f484c5998446a8ab3f103b177530e",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 432x288 with 4 Axes>', 'i…"
+       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 640x480 with 4 Axes>', 'i…"
       ]
      },
      "metadata": {},
@@ -575,7 +573,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -669,13 +667,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6d14da64f46b485a8e9cdc8daffbe2ef",
+       "model_id": "d56612ff3d7a4f99b53d1367c2e80e9d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -689,12 +687,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5f73af8c617146eabee8ea7d272742fb",
+       "model_id": "0d9968ef773b475b96343c60ba4f70c5",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 432x288 with 1 Axes>', 'i…"
+       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 640x480 with 1 Axes>', 'i…"
       ]
      },
      "metadata": {},
@@ -784,9 +782,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }