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<p><font size="4">Please join us for our EOAS Colloquium Speaker,
Dr. Zan Armstrong, Friday Oct 21 at 3pm on ZOOM:</font></p>
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</font></p>
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<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif"><font style="background-color:rgb(255,255,255)" size="5" color="#000000"><u>Guiding Principles for Data
Visualization for Analysis</u></font></p>
<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif"><font style="background-color:rgb(255,255,255)" color="#000000">In
science, we create and look at charts all the time. It's
the primary way that we interact with our data, and make
sense of it. Yet, all too often, investing in data
visualization is seen as a "nice to have", something to
make things "prettier", or something to be done only at
the end of the research when preparing for a presentation
or publication. While data visualization is an important
part of communicating results, it is a critical tool for
analyzing data as well. Changing how we (literally) look
at our data can be the difference between making a
scientific discovery or overlooking the key insight. </font></p>
<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif">One
challenge is that it's not clear how to do it better. And,
it can feel like a whole different skill set, disconnected
from science, algorithms, or our knowledge of what's
important about the data. </p>
<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif"><font style="background-color:rgb(255,255,255)" color="#000000">In
this talk, Data Visualization Specialist Zan Armstrong
will introduce 3 guiding principles which will empower you
to more effectively use data visualization<i> *in
combination with your own domain expertise* </i>to
better understand your own data. These are:</font></p>
<ul class="gmail-pl-5 gmail-list-disc gmail-mb-4" style="box-sizing:border-box;border:0px solid
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<li style="box-sizing:border-box;border:0px solid
currentcolor"><font style="background-color:rgb(255,255,255)" color="#000000">making the important visible</font></li>
<li style="box-sizing:border-box;border:0px solid
currentcolor"><font style="background-color:rgb(255,255,255)" color="#000000">three simple flexible "tools": many
small charts, make color meaningful, and order matters</font></li>
<li style="box-sizing:border-box;border:0px solid
currentcolor"><font style="background-color:rgb(255,255,255)" color="#000000">demonstrating how you can embrace the
complexity of your data rather than aggregate it away.</font></li>
</ul>
<div><span style="color:rgb(0,0,0);font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif">These
are principles that you can put into practice today, using
whatever software you are currently using to create
charts. Be inspired to invest more in how you look at your
data, and learn how to do it more effectively. </span><br>
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<div><font face="Graphik Meetup, -apple-system, system-ui,
Roboto, Helvetica, Arial, sans-serif" color="#000000"><br>
</font></div>
<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
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Zan Armstrong is a data visualization specialist with a
background in data analysis. Through her work, she empowers
people to more effectively use visualization to better
understand whatever data is most important to them.<br>
<br>
Zan's experience includes contributing to scientific
discoveries as a member of Google Research's Applied
Sciences team, tracking covid in wastewater for California's
state and county public health officials and the public,
creating interactive visualization tools for researchers at
Yale, Stanford, and Berkeley,and as a data analyst
forecasting revenue at Google. Zan's work has been published
in Scientific American, and exhibited in the art museums SF
Moma, Cooper Hewitt, and Ars Electronica. She has published
data visualization research in IEEE InfoVis, and spoken at
conferences including OpenVis Conf, Outlier, and SciPy. More
at <a href="https://urldefense.com/v3/__http://zanarmstrong.com__;!!PhOWcWs!xxZlFN8DOstGNdkz-lZAjCMHYQJ-8dSC6OOMDLFN88LI3JToM1dhbsCIrJl5LaTsTOi-AvYg8c7ZQSiXDm-qMIT57g$" moz-do-not-send="true">zanarmstrong.com</a>. </p>
<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
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<p class="gmail-mb-4" style="box-sizing:border-box;border:0px
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1rem;font-family:"Graphik
Meetup",-apple-system,"system-ui",Roboto,Helvetica,Arial,sans-serif">Topic:
Armstrong Seminar<br>
Time: Oct 21, 2022 03:00 PM Eastern Time (US and Canada)<br>
<br>
Join Zoom Meeting<br>
<a class="moz-txt-link-freetext" href="https://fsu.zoom.us/j/94635209136">https://fsu.zoom.us/j/94635209136</a><br>
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Meeting ID: 946 3520 9136<br>
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