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<h1 class="title toc-ignore">Going Beyond</h1>

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<p>Throughout the course, I hope you expand your horizons. Here are some
ways to do that!</p>
<p><strong>Be Your Own Nate Silver</strong> It’s an election year. Given
that you’re in this class, I’m sure you are following along at <a
href="http://fivethirtyeight.com/"
class="uri">http://fivethirtyeight.com/</a> and their model with great
interest. You’re also, of course, listening to their elections podcast –
and definitely the Friday special edition on how they build their model.
I want you to forecast one or more elections. You can find poll data
using the pollstR package (<a
href="https://cran.r-project.org/web/packages/pollstR/vignettes/introduction.html"
class="uri">https://cran.r-project.org/web/packages/pollstR/vignettes/introduction.html</a>)
or other sources (<a
href="http://is-r.tumblr.com/post/36059986744/gathering-realclearpolitics-polling-trends-with"
class="uri">http://is-r.tumblr.com/post/36059986744/gathering-realclearpolitics-polling-trends-with</a>)
and there are plenty of other data sources out there (<a
href="http://guides.library.harvard.edu/c.php?g=310717&amp;p=2072692"
class="uri">http://guides.library.harvard.edu/c.php?g=310717&amp;p=2072692</a>
as just a start – Google around). For this extra credit, 5 points for
getting the correct answer, 5 extra points for explicitly stating the
confidence of your estimates, and 5 points for a clear explanation of
the methodology. 1 point for each thing you do beyond a weighted average
of polls. Because, come on, that’s easy. Scored out of 16. So,
theoretically, you could get extra credit on your extra credit.</p>
<p><strong>Become a Git Addict</strong> Make a github repository for all
of your work in this class! Structure it well, with a homework, lab, and
project section. Inside of each should be a well structured set of
directories (we’ll talk about this). To get this repo up and running,
This requires learning git and github. There are numerous tutorials on
how to do so both as web pages and on youtube (e.g.,<a
href="http://happygitwithr.com/"
class="uri">http://happygitwithr.com/</a> which is one of my favs) - so
find what works for you. I’ll also host a mini-tutorial sometime in the
first few weeks. +1 point on each homework that is submitted as a link.
+10 if you make your repo into a github.io website that is fully
navigable (requires learning some webpage building in R)</p>
<p><strong>Join the Conversation</strong> There are a wealth of great
conversations out there about data science both in and out of biology.
Starting to listen to the conversation will enable you to keep abreast
of how the field is developing, and enable you to learn toolsets that
will put you a cut above your colleagues as you consider new and
sophisticated analyses. I’d recommend checking out sites list <a
href="http://www.r-bloggers.com/"
class="uri">http://www.r-bloggers.com/</a> daily, listening to podcasts
such as Not So Standard Deviations <a
href="https://itunes.apple.com/us/podcast/not-so-standard-deviations/"
class="uri">https://itunes.apple.com/us/podcast/not-so-standard-deviations/</a>
or following different data science/biology luminaries (such as <a
href="http://twitter.com/hadleywickham"><span
class="citation">@hadleywickham</span></a>, <a
href="http://twitter.com/_inundata"><span
class="citation">@_inundata</span></a>, <a
href="http://twitter.com/rdpeng"><span
class="citation">@rdpeng</span></a>, <a
href="http://twitter.com/hspter"><span
class="citation">@hspter</span></a>, <a
href="http://twitter.com/kara_woo"><span
class="citation">@kara_woo</span></a>, <a
href="http://twitter.com/sckottie"><span
class="citation">@sckottie</span></a>, and more). I’ve also made a full
list at <a href="https://twitter.com/jebyrnes/lists/stats-r-on-twitter"
class="uri">https://twitter.com/jebyrnes/lists/stats-r-on-twitter</a>.
There are a ton of other blogs and people who are relevant to what you
are doing for your research, so look around! Each class, I’ll try and
give an opportunity to share neat things you’ve seen in the ether. +1
for each contribution you make to the class. +10 if you end up at <a
href="http://unconf.ropensci.org/">ROpenSci</a>.</p>
<p><strong>Engage in Data Science at UMB</strong> This is a gimme. So,
I’ve started a a UMB R Users Group that has a slack channel at <a
href="https://umbrug.slack.com/"
class="uri">https://umbrug.slack.com/</a>. Join it and the biol607
channel (where we can talk live) for +3 points on your final grade.
Also, there is a Stats Snack group run by the psych department. It meets
Tuesdays in TBA from 12-1. +5 for attending!</p>


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