diff --git a/lecture_material/19-regression-1/19-regression1.ipynb b/lecture_material/19-regression-1/19-regression1.ipynb
index 1b4d776464cee96feaff07987fa405b2b624a805..80f8f5b5f8da7db621f5ed8ec10caebb2cb0cda0 100644
--- a/lecture_material/19-regression-1/19-regression1.ipynb
+++ b/lecture_material/19-regression-1/19-regression1.ipynb
@@ -1529,7 +1529,7 @@
    "source": [
     "#### Explained variance score\n",
     "\n",
-    "- `explained_variance = (known_var - explained_variance) / known_var`\n",
+    "- `explained_variance_score = (known_var - explained_variance) / known_var`\n",
     "    - where `known_var = y_true.var()` and `explained_variance = (y_true - y_pred).var()`"
    ]
   },
@@ -1953,124 +1953,124 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1355</th>\n",
+       "      <th>1203</th>\n",
        "      <td>2022-04-07 19:00:00+00:00</td>\n",
-       "      <td>55073001300</td>\n",
+       "      <td>55079070100</td>\n",
        "      <td>None</td>\n",
-       "      <td>1851</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0.43</td>\n",
-       "      <td>14</td>\n",
+       "      <td>962</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.86</td>\n",
+       "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>1778</td>\n",
-       "      <td>4</td>\n",
+       "      <td>432</td>\n",
+       "      <td>518</td>\n",
        "      <td>2022-04-06 06:00:00+00:00</td>\n",
-       "      <td>6860</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>3425</td>\n",
+       "      <td>4312</td>\n",
+       "      <td>174.0</td>\n",
+       "      <td>2957</td>\n",
        "      <td>Census tract</td>\n",
-       "      <td>1.319813e+08</td>\n",
-       "      <td>47900.136129</td>\n",
-       "      <td>POLYGON ((-89.65378 44.94030, -89.65527 44.941...</td>\n",
+       "      <td>3.024857e+06</td>\n",
+       "      <td>10099.546360</td>\n",
+       "      <td>POLYGON ((-87.90633 43.13312, -87.90820 43.133...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>786</th>\n",
+       "      <th>1191</th>\n",
        "      <td>2022-04-07 19:00:00+00:00</td>\n",
-       "      <td>55025001101</td>\n",
+       "      <td>55079185700</td>\n",
        "      <td>None</td>\n",
-       "      <td>1439</td>\n",
+       "      <td>595</td>\n",
        "      <td>0</td>\n",
-       "      <td>0.43</td>\n",
-       "      <td>1</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>2</td>\n",
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>882</td>\n",
-       "      <td>555</td>\n",
+       "      <td>298</td>\n",
+       "      <td>266</td>\n",
        "      <td>2022-04-06 06:00:00+00:00</td>\n",
-       "      <td>5126</td>\n",
-       "      <td>572.0</td>\n",
-       "      <td>2538</td>\n",
+       "      <td>1877</td>\n",
+       "      <td>383.0</td>\n",
+       "      <td>2945</td>\n",
        "      <td>Census tract</td>\n",
-       "      <td>1.253708e+06</td>\n",
-       "      <td>4697.297158</td>\n",
-       "      <td>POLYGON ((-89.40061 43.07327, -89.40108 43.073...</td>\n",
+       "      <td>1.254436e+06</td>\n",
+       "      <td>4482.212537</td>\n",
+       "      <td>POLYGON ((-87.91698 43.07116, -87.91726 43.071...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>317</th>\n",
+       "      <th>389</th>\n",
        "      <td>2022-04-07 19:00:00+00:00</td>\n",
-       "      <td>55117010900</td>\n",
+       "      <td>55079101200</td>\n",
        "      <td>None</td>\n",
-       "      <td>784</td>\n",
+       "      <td>915</td>\n",
        "      <td>0</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>6</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>33</td>\n",
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>376</td>\n",
-       "      <td>374</td>\n",
+       "      <td>379</td>\n",
+       "      <td>469</td>\n",
        "      <td>2022-04-06 06:00:00+00:00</td>\n",
-       "      <td>3212</td>\n",
-       "      <td>64.0</td>\n",
-       "      <td>1284</td>\n",
+       "      <td>3184</td>\n",
+       "      <td>202.0</td>\n",
+       "      <td>1363</td>\n",
        "      <td>Census tract</td>\n",
-       "      <td>1.811851e+08</td>\n",
-       "      <td>55323.608399</td>\n",
-       "      <td>POLYGON ((-87.85034 43.71829, -87.85192 43.718...</td>\n",
+       "      <td>2.511556e+06</td>\n",
+       "      <td>6796.635429</td>\n",
+       "      <td>POLYGON ((-88.01756 42.98824, -88.01756 42.988...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>665</th>\n",
+       "      <th>448</th>\n",
        "      <td>2022-04-07 19:00:00+00:00</td>\n",
-       "      <td>55059001500</td>\n",
+       "      <td>55079009500</td>\n",
        "      <td>None</td>\n",
-       "      <td>1038</td>\n",
+       "      <td>547</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.43</td>\n",
        "      <td>1</td>\n",
-       "      <td>0.29</td>\n",
-       "      <td>12</td>\n",
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>339</td>\n",
-       "      <td>664</td>\n",
+       "      <td>277</td>\n",
+       "      <td>254</td>\n",
        "      <td>2022-04-06 06:00:00+00:00</td>\n",
-       "      <td>3678</td>\n",
-       "      <td>347.0</td>\n",
-       "      <td>2388</td>\n",
+       "      <td>2113</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>1874</td>\n",
        "      <td>Census tract</td>\n",
-       "      <td>2.606712e+06</td>\n",
-       "      <td>8360.074105</td>\n",
-       "      <td>POLYGON ((-87.84300 42.57762, -87.84324 42.577...</td>\n",
+       "      <td>9.560618e+05</td>\n",
+       "      <td>4005.196264</td>\n",
+       "      <td>POLYGON ((-87.97244 43.05711, -87.97267 43.057...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1108</th>\n",
+       "      <th>1012</th>\n",
        "      <td>2022-04-07 19:00:00+00:00</td>\n",
-       "      <td>55087011900</td>\n",
+       "      <td>55027960300</td>\n",
        "      <td>None</td>\n",
-       "      <td>2326</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0.43</td>\n",
-       "      <td>9</td>\n",
+       "      <td>3879</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.57</td>\n",
+       "      <td>29</td>\n",
        "      <td>0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0</td>\n",
        "      <td>...</td>\n",
-       "      <td>1105</td>\n",
-       "      <td>1168</td>\n",
+       "      <td>1363</td>\n",
+       "      <td>2386</td>\n",
        "      <td>2022-04-06 06:00:00+00:00</td>\n",
-       "      <td>8513</td>\n",
-       "      <td>241.0</td>\n",
-       "      <td>2862</td>\n",
+       "      <td>7928</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>2766</td>\n",
        "      <td>Census tract</td>\n",
-       "      <td>1.683152e+07</td>\n",
-       "      <td>22550.426126</td>\n",
-       "      <td>POLYGON ((-88.28794 44.29778, -88.28930 44.297...</td>\n",
+       "      <td>2.580188e+07</td>\n",
+       "      <td>27162.474970</td>\n",
+       "      <td>POLYGON ((-88.77561 43.59656, -88.77558 43.596...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -2079,46 +2079,46 @@
       ],
       "text/plain": [
        "                         RptDt        GEOID GEOName  POS_CUM_CP  POS_NEW_CP  \\\n",
-       "1355 2022-04-07 19:00:00+00:00  55073001300    None        1851           3   \n",
-       "786  2022-04-07 19:00:00+00:00  55025001101    None        1439           0   \n",
-       "317  2022-04-07 19:00:00+00:00  55117010900    None         784           0   \n",
-       "665  2022-04-07 19:00:00+00:00  55059001500    None        1038           1   \n",
-       "1108 2022-04-07 19:00:00+00:00  55087011900    None        2326           2   \n",
+       "1203 2022-04-07 19:00:00+00:00  55079070100    None         962           0   \n",
+       "1191 2022-04-07 19:00:00+00:00  55079185700    None         595           0   \n",
+       "389  2022-04-07 19:00:00+00:00  55079101200    None         915           0   \n",
+       "448  2022-04-07 19:00:00+00:00  55079009500    None         547           3   \n",
+       "1012 2022-04-07 19:00:00+00:00  55027960300    None        3879           0   \n",
        "\n",
        "      POS_7DAYAVG_CP  DTH_CUM_CP  DTH_NEW_CP  DTH_7DAYAVG_CP  \\\n",
-       "1355            0.43          14           0             0.0   \n",
-       "786             0.43           1           0             0.0   \n",
-       "317             0.00           6           0             0.0   \n",
-       "665             0.29          12           0             0.0   \n",
-       "1108            0.43           9           0             0.0   \n",
+       "1203            0.86           0           0             0.0   \n",
+       "1191            0.00           2           0             0.0   \n",
+       "389             0.29          33           0             0.0   \n",
+       "448             0.43           1           0             0.0   \n",
+       "1012            0.57          29           0             0.0   \n",
        "\n",
        "      DTH_OVER_30DAYS_CP  ...  HOSP_NO_CP HOSP_UNK_CP  \\\n",
-       "1355                   0  ...        1778           4   \n",
-       "786                    0  ...         882         555   \n",
-       "317                    0  ...         376         374   \n",
-       "665                    0  ...         339         664   \n",
-       "1108                   0  ...        1105        1168   \n",
+       "1203                   0  ...         432         518   \n",
+       "1191                   0  ...         298         266   \n",
+       "389                    0  ...         379         469   \n",
+       "448                    0  ...         277         254   \n",
+       "1012                   0  ...        1363        2386   \n",
        "\n",
        "                          Date   POP POP_MOE  OBJECTID           GEO  \\\n",
-       "1355 2022-04-06 06:00:00+00:00  6860    17.0      3425  Census tract   \n",
-       "786  2022-04-06 06:00:00+00:00  5126   572.0      2538  Census tract   \n",
-       "317  2022-04-06 06:00:00+00:00  3212    64.0      1284  Census tract   \n",
-       "665  2022-04-06 06:00:00+00:00  3678   347.0      2388  Census tract   \n",
-       "1108 2022-04-06 06:00:00+00:00  8513   241.0      2862  Census tract   \n",
+       "1203 2022-04-06 06:00:00+00:00  4312   174.0      2957  Census tract   \n",
+       "1191 2022-04-06 06:00:00+00:00  1877   383.0      2945  Census tract   \n",
+       "389  2022-04-06 06:00:00+00:00  3184   202.0      1363  Census tract   \n",
+       "448  2022-04-06 06:00:00+00:00  2113   150.0      1874  Census tract   \n",
+       "1012 2022-04-06 06:00:00+00:00  7928    40.0      2766  Census tract   \n",
        "\n",
        "       ShapeSTArea  ShapeSTLength  \\\n",
-       "1355  1.319813e+08   47900.136129   \n",
-       "786   1.253708e+06    4697.297158   \n",
-       "317   1.811851e+08   55323.608399   \n",
-       "665   2.606712e+06    8360.074105   \n",
-       "1108  1.683152e+07   22550.426126   \n",
+       "1203  3.024857e+06   10099.546360   \n",
+       "1191  1.254436e+06    4482.212537   \n",
+       "389   2.511556e+06    6796.635429   \n",
+       "448   9.560618e+05    4005.196264   \n",
+       "1012  2.580188e+07   27162.474970   \n",
        "\n",
        "                                               geometry  \n",
-       "1355  POLYGON ((-89.65378 44.94030, -89.65527 44.941...  \n",
-       "786   POLYGON ((-89.40061 43.07327, -89.40108 43.073...  \n",
-       "317   POLYGON ((-87.85034 43.71829, -87.85192 43.718...  \n",
-       "665   POLYGON ((-87.84300 42.57762, -87.84324 42.577...  \n",
-       "1108  POLYGON ((-88.28794 44.29778, -88.28930 44.297...  \n",
+       "1203  POLYGON ((-87.90633 43.13312, -87.90820 43.133...  \n",
+       "1191  POLYGON ((-87.91698 43.07116, -87.91726 43.071...  \n",
+       "389   POLYGON ((-88.01756 42.98824, -88.01756 42.988...  \n",
+       "448   POLYGON ((-87.97244 43.05711, -87.97267 43.057...  \n",
+       "1012  POLYGON ((-88.77561 43.59656, -88.77558 43.596...  \n",
        "\n",
        "[5 rows x 90 columns]"
       ]
@@ -2143,7 +2143,7 @@
     {
      "data": {
       "text/plain": [
-       "0.0831457774708616"
+       "0.16858602389122834"
       ]
      },
      "execution_count": 42,
@@ -2195,7 +2195,7 @@
     {
      "data": {
       "text/plain": [
-       "array([0.26352338, 0.09152472, 0.13661195, 0.16246483, 0.23187313])"
+       "array([0.22428886, 0.09466345, 0.25987694, 0.12149025, 0.2110579 ])"
       ]
      },
      "execution_count": 43,
@@ -2220,7 +2220,7 @@
     {
      "data": {
       "text/plain": [
-       "0.17719960013501254"
+       "0.1822754791451171"
       ]
      },
      "execution_count": 44,
@@ -2265,7 +2265,7 @@
     {
      "data": {
       "text/plain": [
-       "0.17719960013501254"
+       "0.1822754791451171"
       ]
      },
      "execution_count": 46,
@@ -2286,7 +2286,7 @@
     {
      "data": {
       "text/plain": [
-       "0.21807191767796894"
+       "0.21847807530968777"
       ]
      },
      "execution_count": 47,
@@ -2324,7 +2324,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 300x300 with 1 Axes>"
       ]
@@ -2356,7 +2356,7 @@
     {
      "data": {
       "text/plain": [
-       "0.06268276746923607"
+       "0.06322381180319962"
       ]
      },
      "execution_count": 49,
@@ -2377,7 +2377,7 @@
     {
      "data": {
       "text/plain": [
-       "0.08567249382616898"
+       "0.06703675246344569"
       ]
      },
      "execution_count": 50,
@@ -2398,8 +2398,8 @@
     {
      "data": {
       "text/plain": [
-       "model1    0.062683\n",
-       "model2    0.085672\n",
+       "model1    0.063224\n",
+       "model2    0.067037\n",
        "dtype: float64"
       ]
      },
@@ -2432,7 +2432,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 300x300 with 1 Axes>"
       ]
@@ -2471,7 +2471,7 @@
     {
      "data": {
       "text/plain": [
-       "0.6986508828086834"
+       "0.675922025742224"
       ]
      },
      "execution_count": 53,
@@ -2507,9 +2507,9 @@
     {
      "data": {
       "text/plain": [
-       "array([-3.30381631e-02, -2.00583421e-03, -1.43858077e-04,  1.35287654e-02,\n",
-       "        2.28067346e-02, -1.84996117e-02,  1.11739705e-02,  3.69129869e-02,\n",
-       "        1.75078600e-01,  2.75258891e-01])"
+       "array([-3.07843136e-02,  2.30136853e-04, -9.79624336e-04,  1.38921261e-02,\n",
+       "        1.65612818e-02, -1.14307223e-02,  6.32603501e-03,  2.87701547e-02,\n",
+       "        1.77580170e-01,  2.86019994e-01])"
       ]
      },
      "execution_count": 54,
@@ -2539,7 +2539,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 300x200 with 1 Axes>"
       ]
diff --git a/lecture_material/19-regression-1/19-regression1_001.ipynb b/lecture_material/19-regression-1/19-regression1_001.ipynb
index 71b6e0ee36b06a1d2f42e02aef40da68e3a70959..2edd0e8a3b04d9bb1c3b38e5b9622920825e7192 100644
--- a/lecture_material/19-regression-1/19-regression1_001.ipynb
+++ b/lecture_material/19-regression-1/19-regression1_001.ipynb
@@ -475,7 +475,7 @@
    "source": [
     "#### Explained variance score\n",
     "\n",
-    "- `explained_variance = (known_var - explained_variance) / known_var`\n",
+    "- `explained_variance_score = (known_var - explained_variance) / known_var`\n",
     "    - where `known_var = y_true.var()` and `explained_variance = (y_true - y_pred).var()`"
    ]
   },
diff --git a/lecture_material/19-regression-1/19-regression1_002.ipynb b/lecture_material/19-regression-1/19-regression1_002.ipynb
index 71b6e0ee36b06a1d2f42e02aef40da68e3a70959..2edd0e8a3b04d9bb1c3b38e5b9622920825e7192 100644
--- a/lecture_material/19-regression-1/19-regression1_002.ipynb
+++ b/lecture_material/19-regression-1/19-regression1_002.ipynb
@@ -475,7 +475,7 @@
    "source": [
     "#### Explained variance score\n",
     "\n",
-    "- `explained_variance = (known_var - explained_variance) / known_var`\n",
+    "- `explained_variance_score = (known_var - explained_variance) / known_var`\n",
     "    - where `known_var = y_true.var()` and `explained_variance = (y_true - y_pred).var()`"
    ]
   },