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<p><mark>The course website for STA130 Winter 2019 can be found on <a href="https://q.utoronto.ca">Quercus</a> </mark></p>
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<p><br> <br> <br></p>
<div id="midterm-test-information" class="section level2">
<h2><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> Midterm Test Information</h2>
<p>Midterm test information is available <a href="Fall2018/term_test_Fall2018.html">here</a>.</p>
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<div id="ta-office-hours" class="section level2">
<h2><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> TA Office Hours</h2>
<p>TA office hours will be held in SS623B (Sidney Smith lower level).</p>
<p><strong>Schedule for TA office hours after December 6</strong></p>
<ul>
<li>Thursday, December 13, 11am-1pm</li>
<li>Friday, December 14, 11am-1pm</li>
<li>Monday, December, 17, 2-5pm</li>
<li>Tuesday, December 18, 2-5pm</li>
</ul>
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<p>Weekly office hours will be held on:</p>
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<li>Wednesday: 14:00 - 17:00</li>
<li>Thursday: 11:00 - 13:00</li>
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<h2><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> Instructors</h2>
<p><a href="https://utstat.toronto.edu/~nathan/">Professor Nathan Taback</a> and Professor Nathalie Moon.</p>
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<div id="syllabus" class="section level2">
<h2><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> Syllabus</h2>
<p>Important information about the course can found on the <a href="Fall2018/STA130syllabus2018S-Fall2018.html">Fall 2018 syllabus</a>.</p>
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<p>Important course dates can be found in the <a href="Fall2018/STA130-Fall2018-Calendar.html">course calender</a>.</p>
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<div id="computing" class="section level2">
<h2><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> Computing</h2>
<p>The course will use <a href="https://www.r-project.org">R</a> for computing. R is freely available <a href="https://cran.utstat.utoronto.ca">here</a>. We recommend using <a href="https://www.rstudio.com">R Studio</a> which can be <a href="https://cran.utstat.utoronto.ca">downloaded</a> for free. We will use <a href="https://rmarkdown.rstudio.com">R Markdown</a> as an authoring framework for creating reproducible data science documents.</p>
<div id="getting-started-with-r" class="section level3">
<h3><span class="glyphicon glyphicon-chevron-right" aria-hidden="true"></span> Getting Started with R</h3>
<ul>
<li>If you have never programmed before then <a href="https://d1b10bmlvqabco.cloudfront.net/attach/ighbo26t3ua52t/igp9099yy4v10/igz7vp4w5su9/OReilly_HandsOn_Programming_with_R_2014.pdf">Hands-On Programming with R, by Garrett Grolemund</a> is a great place to start.</li>
<li><a href="https://r4ds.had.co.nz">R for Data Science, by Hadley Wickham and Garrett Grolemund</a> is a wonderful resource.</li>
<li>A list of more resources is available on the course website <a href="R_resources.html">here</a>.</li>
</ul>
</div>
<div id="rstudio-cloud-or-rstudio-desktop" class="section level3">
<h3>RStudio Cloud or RStudio Desktop</h3>
<ol style="list-style-type: decimal">
<li><p>Students in the course will be able to do all computing on R Studio Cloud <a href="https://rstudio.cloud" class="uri">https://rstudio.cloud</a></p></li>
<li><p>Another alternative is to install RStudio on your own computer. You will need to download <a href="https://cran.utstat.utoronto.ca">R</a> then <a href="https://www.rstudio.com/products/rstudio/download/#download">RStudio</a>.</p></li>
</ol>
<p><a rel="license" href="https://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons Licence" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This website is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</p>
<p>R Markdown source for this website <a href="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/ntaback/UofT_STA130"> <i class="fa fa-github fa-2x" aria-hidden="true"></i> </a></p>
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