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<span style="font-size:16.0pt;font-family:"Calibri Light",sans-serif;color:#2C6EAB">ECOL 596W -- Programming for Data Analysis in R (Spring 2016) – 2 units</span><o:p></o:p></h1>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Ty Taylor and Scott Saleska</span><o:p></o:p></p>
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<span style="font-size:14.0pt;font-family:"Calibri Light",sans-serif;color:#2C6EAB">Initial meeting/proposed course time: Friday 10-11:30, BSW 302</span><o:p></o:p></h1>
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<span style="font-size:14.0pt;font-family:"Calibri Light",sans-serif;color:#2C6EAB">Starting January 15</span><o:p></o:p></h1>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:9.5pt">Contacts and enrollment</span></b><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-family:"Calibri",sans-serif">For all inquiries about the course, please send an email to both Ty Taylor (<a href="mailto:tytaylor@email.arizona.edu" target="_blank">tytaylor@email.arizona.edu</a>)
and Scott Saleska (<a href="mailto:saleska@email.arizona.edu" target="_blank">saleska@email.arizona.edu</a>). </span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-family:"Calibri",sans-serif">If you are interested in registering for the course, then please contact EEB’s Grad Coordinator, Pennie Rabago, at <a href="mailto:pliebig@email.arizona.edu" target="_blank">pliebig@email.arizona.edu</a>.</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-family:"Calibri",sans-serif">The course will be offered for 2 units. Registration is open to graduates and advanced undergraduates with permission.</span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Course summary</span></b><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">This course will teach the fundamentals of programming for data analysis in R. The course emphasis is practical,
providing skills for more effective research and encouraging immediate application to students’ own work.</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">The course is based on a unique set of tutorials that provide a complete foundation of techniques in R, which are
broadly applicable across research disciplines. We start from the very beginning, and build toward powerful techniques such as fast iteration of custom functions. We will apply a variety of packaged and custom statistical tests. The latest iteration of course
tutorials and outline are available at the following link, but note that these will be updated throughout the course: <a href="http://www.saleskalab.org/teaching/tutorials/r-tutorials/" target="_blank">http://www.saleskalab.org/teaching/tutorials/r-tutorials/</a></span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">What is R?</span></b><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">R should be thought of as a language for analyzing data. Creative and thorough data analysis involves not only statistical
tests, but complex manipulation of datasets, e.g., merging multiple data sources, assessing nested structures, interactions, alternative conditions, data gaps, etc. Very few datasets are simple enough to fully explore and understand by manual manipulation
in spreadsheet programs like Excel. Programming solves these problems. An R “script” records all analysis steps, both in English (via comments) and in R language (via code), while also performing the analysis.</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">This course teaches a complete foundation of analysis techniques in R. We will alternate between practical examples
of exploratory analysis of complex datasets, and specific statistical tests.</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Teaching method</span></b><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">R is a foreign language. As other introductory programming and foreign language courses are taught, this course uses
‘repeat after me’ class exercises. We will teach the principles—the meanings of the terms and the syntax that links terms into functional sentences—and students will follow along in typing in the code corresponding to each example in a neatly formatted R script.
This will build muscle memory as students practice ‘speaking the language’, allowing observation of the results on their own screens. The course provides practical exercises, done in class in groups, and/or independently as homework. Students are expected
to work toward a final project that creatively applies lessons of the course to unique questions in real datasets (including from students’ own research).</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:7.5pt">---------------------------------<br>
A. Elizabeth (Betsy) Arnold<br>
School of Plant Sciences<br>
The University of Arizona<br>
Tucson, AZ 85721<br>
<br>
<a href="http://arnoldlab.net" target="_blank">http://arnoldlab.net</a><br>
<a href="mailto:barnoldaz@gmail.com" target="_blank">barnoldaz@gmail.com</a></span><o:p></o:p></p>
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