typo in weekly material

doc/LectureNotes/_build/html/week36.html

@@ -397,8 +397,8 @@ const thebe_selector_output = ".output, .cell_output"
   </a>
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  <li class="toc-h2 nav-item toc-entry">
-  <a class="reference internal nav-link" href="#independent-and-identically-distrubuted-iid">
-   Independent and Identically Distrubuted (iid)
+  <a class="reference internal nav-link" href="#independent-and-identically-distributed-iid">
+   Independent and Identically Distributed (iid)
   </a>
  </li>
  <li class="toc-h2 nav-item toc-entry">
@@ -668,8 +668,8 @@ const thebe_selector_output = ".output, .cell_output"
   </a>
  </li>
  <li class="toc-h2 nav-item toc-entry">
-  <a class="reference internal nav-link" href="#independent-and-identically-distrubuted-iid">
-   Independent and Identically Distrubuted (iid)
+  <a class="reference internal nav-link" href="#independent-and-identically-distributed-iid">
+   Independent and Identically Distributed (iid)
   </a>
  </li>
  <li class="toc-h2 nav-item toc-entry">
@@ -1854,8 +1854,8 @@ single output <span class="math notranslate nohighlight">\(y_i\)</span> is given
 y_i\sim \mathcal{N}(\boldsymbol{X}_{i,*}\boldsymbol{\beta}, \sigma^2)=\frac{1}{\sqrt{2\pi\sigma^2}}\exp{\left[-\frac{(y_i-\boldsymbol{X}_{i,*}\boldsymbol{\beta})^2}{2\sigma^2}\right]}.
 \]</div>
 </div>
-<div class="section" id="independent-and-identically-distrubuted-iid">
-<h2>Independent and Identically Distrubuted (iid)<a class="headerlink" href="#independent-and-identically-distrubuted-iid" title="Permalink to this headline">¶</a></h2>
+<div class="section" id="independent-and-identically-distributed-iid">
+<h2>Independent and Identically Distributed (iid)<a class="headerlink" href="#independent-and-identically-distributed-iid" title="Permalink to this headline">¶</a></h2>
 <p>We assume now that the various <span class="math notranslate nohighlight">\(y_i\)</span> values are stochastically distributed according to the above Gaussian distribution.
 We define this distribution as</p>
 <div class="math notranslate nohighlight">

doc/LectureNotes/_build/jupyter_execute/week36.py

@@ -782,7 +782,7 @@ plt.show()
 # y_i\sim \mathcal{N}(\boldsymbol{X}_{i,*}\boldsymbol{\beta}, \sigma^2)=\frac{1}{\sqrt{2\pi\sigma^2}}\exp{\left[-\frac{(y_i-\boldsymbol{X}_{i,*}\boldsymbol{\beta})^2}{2\sigma^2}\right]}.
 # $$
 
-# ## Independent and Identically Distrubuted (iid)
+# ## Independent and Identically Distributed (iid)
 # 
 # We assume now that the various $y_i$ values are stochastically distributed according to the above Gaussian distribution. 
 # We define this distribution as