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homeworks/reflect.html

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<small>Credit: public domain</small>
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<h1>Homework 10 - Reflect</h1>
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<div class="lead">Benjamin Xie & Greg Nelson</div>
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<div class="lead">Greg Nelson (with material by Benjamin Xie)</div>
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<p>Individually, write a roughly <strong>500 word statement</strong> covering the following:</p>
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<li>Do you believe any of your teammates do not deserve full credit for your team's success? Why? What percent of the credit do you think they deserve?</li>
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</ul>
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<p>You'll submit this report on your <b>personal</b> Google Drive folder..</p>
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<p>You'll submit this report on your <b>personal</b> Google Drive folder. You can write your statement in paragraphs or you can copy-paste the questions and then answer them one by one.</p>
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<h2>Grading criteria</h2>
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index.html

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Evaluating quality of model parameters (fitted models)
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<!--Finding models for decision-making using computer simulations-->
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<ul>
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<li>Slides: <a href="https://docs.google.com/presentation/d/10Xv1Ecldx38umSGE-RISzscL6HRTwzYsi-9I93K1XwQ/edit?usp=sharing" target="_blank"></a></li>
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<li>Code: <a href="https://github.com/info370/fa17-labs/tree/master/class/6.3" target="_blank"></a></li>
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<li>Slides: <a href="https://docs.google.com/presentation/d/1P40dNddzuxbCG91jwOEJmBI-VReZmF6DmTNSzkWJPQE/edit?usp=sharing" target="_blank">Slides</a></li>
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<li>Code: <a href="https://github.com/Info-370-Winter-2018/class_examples" target="_blank">Bootstrapping and Monte Carlo Simulations</a></li>
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</ul>
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<ul>
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<li>Assigned: Project Milestone 4: Project Review. Due <del>Mon 2/12</del> Friday 2/16.</li>
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<li>Assigned: Project Milestone 5: Project Revision. Due Monday 2/19.</li>
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<li>Assigned: <a href="https://docs.google.com/document/d/1Yan1Ndfy5kxMhfPkF7fhQMYjyxHBNvL6XllNRW8lGmQ/edit?usp=sharing">Homework 6</a>. Due Friday Feb 23.</li>
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<li>Assigned: <a href="http://www.greglnelson.info/info370/project/proposal-review.html">Project Milestone 4: Project Review</a>. Due <del>Mon 2/12</del> Friday 2/16.</li>
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<li>Assigned: <a href="project/proposal-revision.html">Project Milestone 5: Project Revision</a>. Due <del>Mon 2/19</del> Tuesday 2/20.</li>
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<li>Assigned: <a href="project/project-meeting.html">Project Milestone 6: Project check-in meetings</a>. Due Tues 2/20. </li>
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<li>Assigned: Project Milestone 7 & 8: <a href="project/presentation.html">Presentation</a> & <a href="project/artifact.html">Artifact</a>. Due during finals week or last week of classes.</li>
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<li>Assigned: Project Milestone 7 & 8: <a href="project/presentation.html">Presentation</a> & <a href="project/artifact.html">Artifact</a>. Due by end of day on day of finals (March 13).</li>
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</ul>
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</td>
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<!-- QUARTERLY -->
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<td>2/19</td><td>Holiday</td>
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<td>
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<ul>
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<li>Reading: Models and Simulations for Decision-making</li>
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</ul>
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</td>
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</tr>
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<tr >
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<td>
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<!--Model fit, overfitting and cross-validation-->
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<!--Common models and how to use them-->
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Interpreting models and using them for decisions
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Logistic Regression; Evaluating models with cross-validation
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<ul>
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<li>Note: Greg will be at a conference</li>
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<li>Reading: Case studies of data science for decisions</li>
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<li>Reading: <a href="https://docs.google.com/document/d/1JJKH71y-Axm41-IDcaBjQ44wC1YfYL-J8rTYmAGWOBQ/edit?usp=sharing">Logistic regression; cross-validation and overfitting</a></li>
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</ul>
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</td>
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<!-- QUARTERLY -->
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<td>2/26</td><td>Lecture</td>
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<td>
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Using simulations to understand new types of models
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Logistic Regression; simulating decisions using models and residuals
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<ul>
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<li>Reading: Using simulations to understand logistic regression <a href=""></a></li>
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<!--<li>Reading: Using simulations to understand logistic regression <a href=""></a></li><-->
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<li>Slides: <a href="https://docs.google.com/presentation/d/1u517LRSLY-mDwBr5n2T6S14qGqbYf6PZNsVqYTbMPQw/edit?usp=sharing">Slides</a></li>
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<li>Code: <a href="https://github.com/Info-370-Winter-2018/class_examples">see 8.2 Filled In</a></li>
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</ul>
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</td>
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</tr>
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<tr>
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<td>2/26</td><td>Lab</td>
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<td>
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Trying different models on your data
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Trying different thresholds for logistic regression and simulating decisions
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<ul>
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<li>Code: Comparing models <a href="https://github.com/info370/fa17-labs/tree/master/class/8.1" target="_blank"></a></li>
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<li>Code: <a href="https://github.com/Info-370-Winter-2018/class_examples">see 8.1 (not filled in) </a></li>
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</ul>
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</td>
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</tr>
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<tr>
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<!-- QUARTERLY -->
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<td>2/28</td><td>Lecture</td>
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<td>
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Communicating data science
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Bias; Simulating decision using models and residuals
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<ul>
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<li>Reading: Examples of communicating data science<a href=""></a></li>
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<li>Slides: <a href="https://docs.google.com/presentation/d/1xxAK8KfgzwKEW-ISEgN0JbcxNEu_2szFWoRrHCyF_LI/edit?usp=sharing">Slides</a></li>
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<li>Code: <a href="https://github.com/Info-370-Winter-2018/class_examples">see simulating decision for class 8.3 and class 8.2 filled in</a></li>
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</ul>
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</td>
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</tr>
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<!--<tr><td colspan=3 class="text-uppercase lead">Week 9 &mdash; Big Data and Opacity </td></tr>-->
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<tr><td colspan=3 class="text-uppercase lead">Week 9 &mdash; Interpreting Big Data </td></tr>
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<tr><td colspan=3 class="text-uppercase lead">Week 9 &mdash; Debugging and Limitations of Models</td></tr>
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<tr >
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<!-- QUARTERLY -->
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<td>3/5</td><td>Lecture</td>
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<td>
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Debugging strategies for R code and Monte Carlo Simulations
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<!--Scaling to "Big Data"-->
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<ul>
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<!--<li>Reading: Excerpt from Fourth Paradigm; Business Articles on Big Data</li>-->
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<!-- <li>Activity (110 min): <a href="activities/work.html">Work time</a></li> -->
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<li>Reading: Excerpt from Antifragile, big data and opacity</li>
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<li>Supplemental Reading:
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<a href="https://github.com/berkeley-scf/tutorial-R-debugging/blob/master/R-debugging.Rmd">Debugging in R</a>,
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<a href="https://web.stanford.edu/class/archive/cs/cs106a/cs106a.1134/handouts/250%20Debugging%20Strategies.pdf">Debugging Mindset</a>,
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<a href="https://bookdown.org/rdpeng/rprogdatascience/">Examples of R language features</a> </li>
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<li>Slides: <a href="https://docs.google.com/presentation/d/1v0U22VILRM4QaHJicT15ls5Z0KDP6NOqdzs000THZ1Q/edit?usp=sharing">Slides</a></li>
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<li>Code: <a href="https://github.com/Info-370-Winter-2018/class_examples">See code for 9-1</a></li>
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</ul>
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</td>
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<tr>
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<!-- QUARTERLY -->
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<td>3/7</td><td>Lecture</td>
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<td>
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Reflecting on class projects
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Interpreting models and limitations; reflecting on class projects
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<ul>
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<!--<li>Reading: Excerpt from Antifragile and Simulations</li>-->
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<li>Reading: Reflections from data scientists</li>
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<li>Optional but encouraged Reading: Excerpt from Antifragile, big data and opacity</li>
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</ul>
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</td>
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</tr>
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<tr><td colspan=3 class="text-uppercase lead">Week 10 &mdash; Project Fair </td></tr>
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>
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<!-- QUARTERLY -->
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<td>3/13 Tues</td><td>Project Fair</td>
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<td>
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Room
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</td>
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</tr>
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<tr><td colspan=3 class="text-uppercase lead">Finals week</td></tr>
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<td colspan="4"><a href="homeworks/reflect.html">Homework 9 (Project and Course Reflection)</a> Due 3/14. <br/> We may hold presentations on the date of finals depending on number of groups.</td>
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<td colspan="4"><a href="homeworks/reflect.html">Homework 9 (Project and Course Reflection)</a> Due 3/14. <br/></td>
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</table>
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</p>
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<h2 id="teams">Project Teams</h2>
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<li><a href="https://github.com/info370/project-dataplus" target="_blank">#data PLUS</a> <small>(mentor: Benji)</small></li>
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<li><a href="https://github.com/info370/project-team-cups" target="_blank">Cups</a> <small>(mentor: Greg)</small></li>
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<li><a href="https://github.com/info370/project-dataseyance" target="_blank">Data Seyance</a> <small>(mentor: Greg)</small></li>
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<li><a href="https://github.com/info370/project-es3" target="_blank">ES3</a> <small>(mentor: Greg)</small></li>
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<li><a href="https://github.com/info370/project-fragile-families" target="_blank">Fragile Families</a> <small>(mentor: Benji)</small></li>
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<li><a href="https://github.com/info370/project-jaakt" target="_blank">JAAKT</a> <small>(mentor: Greg)</small></li>
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<li><a href="https://github.com/info370/project-teamawesomeii" target="_blank">Team Awesome 2: The Rise of Suraj</a> <small>(mentor: Benji)</small></li>
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<li><a href="https://github.com/info370/project-teamname-v2" target="_blank">Team Name V2</a> <small>(mentor: Benji)</small></li>
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<ul>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-quokka" target="_blank">#Quokka </a> </li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-giraffekittens" target="_blank">Giraffe-kittens</a> </li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-seaotters" target="_blank">Sea Otters</a></li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-tamagotchu" target="_blank">Tamagotchu</a></li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-honeybadger" target="_blank">Honey Badger</a></li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-platypus" target="_blank">Platypus</a> </li>
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<li><a href="https://github.com/Info-370-Winter-2018/group-formation-for-projects-team-awesome-possum" target="_blank">Awesome Possum</a> </li>
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<li><a href="https://github.com/Info-370-Winter-2018/Team-Crabs-Repo" target="_blank">Crabs</a></li>
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-->
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<h2 id="resources">Resources</h2>
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project/artifact.html

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<img src="../images/book-spiral_publicdomain.jpg" class="img-responsive" />
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<small>Credit: Public Domain</small>
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<h1>Milestone 6: Archive</h1>
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<div class="lead">Benjamin Xie & Gregory L. Nelson</div>
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<h1>Milestone 8: Archive</h1>
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<div class="lead">Gregory L. Nelson (with material made by Benji Xie)</div>
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<p>
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For your final project, you will create 2 things:
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Your target audience should know just enough to be more confident they are making a decision that better optimizes what they want.
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They may be confused or misled by excessive detail or make incorrect conclusions with insufficient detail.
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Finding the appropriate balance is dependent on your decision context and target audience.
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Your artifact might be a Shiny app, a web page made from an R markdown document, or another kind of artifact to communicate your results to decision makers.
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</p>
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<h2>Deliverable 2: Technical Description</h2>
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The target audience for the technical description is other data scientists who wish to interpret, critique, and build off of your work.
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It will be a written report in the form of a page on your GitHub wiki and should provide sufficient detail so somebody can understand your analysis and interpret it.
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It will be a written report in the form of an R markdown document; you should link to a compiled html version in your Github repository, from a page on your GitHub wiki and should provide sufficient detail so somebody can understand your analysis and interpret it.
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</p>
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<!--<p id="ko">Ko, A. J., LaToza, T. D., &amp; Burnett, M. M. (2015). A practical guide to controlled experiments of software engineering tools with human participants. <i>Empirical Software Engineering</i>, <i>20</i>(1), 110-141. <a href="https://doi.org/10.1007/s10664-013-9279-3" target="_blank">https://doi.org/10.1007/s10664-013-9279-3</a></p>-->
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project/presentation.html

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<small>Credit: StockSnap</small>
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<h1>Milestone 7: Presentation</h1>
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<div class="lead">Benjamin Xie & Gregory L. Nelson</div>
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<div class="lead">Gregory L. Nelson (based on material made with Benjamin Xie)</div>
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An important part of any data scientist's job is to share your process and results with your peers and receive feedback.
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</p>
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<ul>
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<li>Not stating the decision context and question to answer.</li>
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<li>Presenting data or analysis in graphs/charts without interpreting it (describing it like you interpreted in tab 1.2).</li>
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<li>Not connecting your analysis to the decision context and question to answer.</li>
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<li>Running out of time without finishing your presentation.</li>
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<li>Slides are too dense and audience is too fixated on reading slides and stopped listening to presenter. (<a href="https://en.wikipedia.org/wiki/Split_attention_effect" target="_blank">split attention effect</a>)</li>
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<small>While an old video (pre-dates laser pointers!), this is Benji's favorite resource on how to speak. This is an investment in your future.</small></p>
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</body>
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project/project-meeting.html

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<small>Credit: Chang Zun Shi</small>
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<h1>Milestone 6: Project Check-In Meeting</h1>
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<div class="lead">Benjamin Xie & Gregory L. Nelson</div>
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<div class="lead">Gregory L. Nelson (based on material made with Benjamin Xie)</div>
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<p>
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Now that your project proposals are complete and we know what decision you want to inform and how, we'll want to meet with you to clarify questions and ensure you can see your project through.
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We will also provide you with guidelines of our expectations for you and this project.
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We will also provide you with guidelines of our expectations for you and this project, and answer specific questions about how the final deliverables will be graded/evaluated.
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By the end of this meeting, we (the instructors) and you and your team should by on the same page regarding what needs to be done and how.
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<h2>Step 1: Prepare for meeting with instructor</h2>
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You'll want to schedule time (we'll send out a Doodle poll or equivalent) with the instructor who will mentor your project.
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Find a time where multiple team members (preferably all) can make.
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Preferably we will meet on Monday Feb 19 in person, but due to your schedule constraints we may need to meet via Skype during the week.
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<ul>
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<li>question about project or deliverable</li>
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<li>concern about project - for example, how well it will fit into your portfolio</li>
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<!--<p id="ko">Ko, A. J., LaToza, T. D., &amp; Burnett, M. M. (2015). A practical guide to controlled experiments of software engineering tools with human participants. <i>Empirical Software Engineering</i>, <i>20</i>(1), 110-141. <a href="https://doi.org/10.1007/s10664-013-9279-3" target="_blank">https://doi.org/10.1007/s10664-013-9279-3</a></p>-->
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project/proposal-review.html

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<small>Credit: StockSnap</small>
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<h1>Milestone 4: Proposal Review</h1>
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<div class="lead">Benjamin Xie & Gregory L. Nelson</div>
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<div class="lead">Gregory L. Nelson</div>
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<p>
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Now that every team has submitted a proposal, it's time to help each other get better by providing peer feedback.
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Now that every team has submitted a proposal (your project spreadsheet), it's time to help each other get better by providing peer feedback.
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<i><a href="#kreiman">Peer review</a></i> is a critical part to improving writing in both academic and industry settings.
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The objective of this assignment is to give you an opportunity to practice providing and receive constructive feedback from your peers.
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This feedback should help you and others think more thoroughly on the project proposals.
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<h2>Step 1: Understand how to provide quality feedback</h2>
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The objective of feedback in peer review is to <b>improve the quality of the writing</b>.
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The objective of feedback in peer review is to <b>improve the quality of writing/thinking</b>.
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In this way, you are very much "on the same team" as the authors of the writing you are reviewing.
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The feedback you provide should help other teams further develop their project proposal.
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Your guiding principle as you provide peer-feedback is this: <b>How can the authors use this feedback to improve their writing</b>?
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Your guiding principle as you provide peer-feedback is this: <b>How can the authors use this feedback to improve their writing/thinking</b>?
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<h2>Step 2: Provide feedback to your peers' project proposals</h2>
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The proposals can be found in the wikis of each <a href="../index.html#teams">project team's GitHub repository</a>.
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The proposals can be found in the wikis of each <a href="../index.html#teams">project team's GitHub repository</a>. For peer review, look at each team's current data science diagram (should be linked on their “Project Scope and Framing” wiki page) then look at their spreadsheet (also linked on their "Project Scope and Framing” wiki page). <b>Do not go back to earlier spreadsheets or wiki pages - only look at their latest spreadsheet</b>. Read first the rows on the domain and the decision/choices (these are below the 1.1-1.4 and 2.1-2.3 questions). then go to the overall questions on feasibility and impact (1.1-1.4 and 2.1-2.3 questions), then looking at the tabs.
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