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00_setup.html

@@ -448,10 +448,9 @@ <h2 class="anchored" data-anchor-id="setting-up-for-methods-camp">Setting up for
 <p>Below are RStudio projects for you to download, available as .zip compressed files. On MacOS, the file will be uncompressed automatically. On Windows, you should do <code>Right click &gt; Extract all</code>.</p>
 <ul>
 <li><a href="materials/methodscamp_part1.zip">Download Part 1 of the class materials</a>.</li>
-<li></li>
+<li><a href="materials/methodscamp_part2.zip">Download Part 2 of the class materials</a>.</li>
 </ul>
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-- [Download Part 2 of the class materials](materials/methodscamp_part2.zip).
 - [Download Part 3 of the class materials](materials/methodscamp_part3.zip).
 - [Download Part 4 of the class materials](materials/methodscamp_part4.zip).
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08_stats_sims.html

@@ -490,10 +490,10 @@ <h4 class="unnumbered anchored" data-anchor-id="uniform-distribution">Uniform di
 <div class="cell">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="fu">runif</span>(<span class="at">n =</span> <span class="dv">20</span>, <span class="at">min =</span> <span class="sc">-</span><span class="dv">3</span>, <span class="at">max =</span> <span class="dv">3</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code> [1] -0.4147353 -1.7086597  0.8332882  0.4711878 -0.4847333  1.9697939
- [7]  0.7394187 -2.2423425 -2.2342682  2.2550012  1.9964924  2.9551739
-[13]  0.9346351  1.0903529  2.9074590 -0.2159666  2.9989812 -2.6390831
-[19]  2.5542698 -2.9149169</code></pre>
+<pre><code> [1] -1.4697646 -0.8779511  2.7009423  1.9463196 -2.3497930  1.9010895
+ [7]  2.9995159 -0.3944635  0.1506044 -1.4701718 -0.5056155 -0.1600914
+[13] -0.4281386 -1.8716729 -1.9186367 -1.9883803 -1.2887057  0.5855176
+[19] -2.0259530 -1.8345219</code></pre>
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 </div>
 <p>When we draw a million times from the distribution, we can then plot it and see that it does look as we would expect:</p>

Methods-Camp.pdf

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     <loc>https://methodscamp.github.io/index.html</loc>
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     <loc>https://methodscamp.github.io/00_setup.html</loc>
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   <url>
     <loc>https://methodscamp.github.io/01_r_intro.html</loc>
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     <loc>https://methodscamp.github.io/02_tidy_data1.html</loc>
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     <loc>https://methodscamp.github.io/03_functions.html</loc>
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     <loc>https://methodscamp.github.io/04_calculus.html</loc>
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     <loc>https://methodscamp.github.io/05_matrices.html</loc>
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     <loc>https://methodscamp.github.io/06_tidy_data2.html</loc>
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     <loc>https://methodscamp.github.io/07_probability.html</loc>
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     <loc>https://methodscamp.github.io/08_stats_sims.html</loc>
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   </url>
   <url>
     <loc>https://methodscamp.github.io/references.html</loc>
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+    <lastmod>2025-08-19T04:04:26.089Z</lastmod>
   </url>
   <url>
     <loc>https://methodscamp.github.io/Methods-Camp.pdf</loc>
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