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DS-100 · Jul 18, 2023 · 4960241 · 4960241
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diff --git a/_images/bus_modeling_30_0.svg b/_images/bus_modeling_30_0.svg
diff --git a/_images/theory_election_28_0.svg b/_images/theory_election_28_0.svg
diff --git a/_images/theory_measurement_error_17_0.svg b/_images/theory_measurement_error_17_0.svg
diff --git a/_images/theory_measurement_error_6_0.svg b/_images/theory_measurement_error_6_0.svg
diff --git a/_sources/ch/03/theory_election.ipynb b/_sources/ch/03/theory_election.ipynb
diff --git a/_sources/ch/03/theory_measurement_error.ipynb b/_sources/ch/03/theory_measurement_error.ipynb
diff --git a/_sources/ch/05/bus_modeling.ipynb b/_sources/ch/05/bus_modeling.ipynb
diff --git a/ch/05/bus_modeling.html b/ch/05/bus_modeling.html
@@ -1396,7 +1396,7 @@ <h1><span class="section-number">5.4. </span>Modeling Wait Times<a class="header
                    <span class="n">width</span><span class="o">=</span><span class="mi">450</span><span class="p">,</span> <span class="n">height</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span>
 
 <span class="n">fig</span><span class="o">.</span><span class="n">update_xaxes</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="s2">&quot;Simulated wait times for 100,000 passengers&quot;</span><span class="p">)</span>
-<span class="n">fig</span><span class="o">.</span><span class="n">update_yaxes</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="s2">&quot;Proportion&quot;</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">update_yaxes</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="s2">&quot;proportion&quot;</span><span class="p">)</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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@@ -1421,12 +1421,12 @@ <h1><span class="section-number">5.4. </span>Modeling Wait Times<a class="header
 While our model captures the typical wait time, we also  want to provide an estimate of the variability in the process. This topic is covered in <a class="reference internal" href="../17/inf_pred_gen_intro.html#ch-inf-pred-theory"><span class="std std-numref">Chapter 17</span></a>.  We can compute the upper quartile of wait times to give us a sense of variability:</p>
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-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Upper quartile wait time: </span><span class="si">{</span><span class="n">np</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">sim_wait_times</span><span class="p">,</span><span class="w"> </span><span class="mf">0.75</span><span class="p">)</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> minutes&quot;</span><span class="p">)</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Upper quartile: </span><span class="si">{</span><span class="n">np</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="n">sim_wait_times</span><span class="p">,</span><span class="w"> </span><span class="mf">0.75</span><span class="p">)</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> minutes&quot;</span><span class="p">)</span>
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Upper quartile wait time: 10.62 minutes
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Upper quartile: 10.62 minutes
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