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week04.html
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<!-- Adapted from https://www.evl.uic.edu/aej/424/ -->
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<title>CS5331</title>
</head>
<body bgcolor="white" text="black">
<span style="font-family: Helvetica,Arial,sans-serif;">
<p>Retinal variables:</p>
<ul>
<li>Size </li>
<li>Value (saturation/opacity) </li>
<li>Orientation </li>
<li>Texture </li>
<li>Shape </li>
<li>Position </li>
<li>Color </li>
</ul>
</span>
<p style="font-family: Helvetica,Arial,sans-serif; text-align:
justify;"><center><img style="width: 65%" alt="retinal
variables" src="https://www.evl.uic.edu/aej/424/pics/week4/a1.png"></center></p>
<span style="font-family: Helvetica,Arial,sans-serif;">
<p>Two types of retinal variables:</p>
<ul>
<li>An <b>associative</b> variable does not affect the visibility of other dimensions (e.g. we can recognize color regardless of orientation.)
<br> Hue, Orientation, Texture, Shape, Position are associative.</li>
<br>
<li>A <b>dissociative</b> variable significantly affect the visibility of other dimensions (e.g. its hard to determine color of a thin line or small dot).<br>
Size and Value are dissociative (they dominate perception and disrupt processing of other correlated dimensions)
</li>
</ul>
</span>
<center><img style="border: 0px solid ; width: 320px; height:
660px;" alt="Orientation" src="https://www.evl.uic.edu/aej/424/pics/week4/a2.png"> </p></center>
<span style="font-family: Helvetica,Arial,sans-serif;">
Scale of measurement for each variable:
<ul>
<li>Categorical: Distinct categories should be obvious. For example, different states, jobs, or students.<br>
Which variables can be used for categorical scale?
</li>
<br>
<li>Ordered: Determine relative ordering. For example, you rate your professor on the scale: good, medium, bad<br>
Position, size, and value are ordered
</li>
<br>
<li>Quantitative: Determine amount of difference between
ordered values. For example, family income in US dollars.<br>
Position and size are quantitative
</li>
</ul>
</span>
</ul>
<br>
<center><img style="width: 50%;" src="https://www.evl.uic.edu/aej/424/pics/week4/v3.jpg"
alt=""></center><br>
<br>
<center><img style="width: 50%;" src="https://www.evl.uic.edu/aej/424/pics/week4/v4.jpg"></center><br>
<br>
<center><img style="width: 60%;" src="https://www.evl.uic.edu/aej/424/pics/week4/v1.jpg"></center><br>
<center><img style="width: 30%;" src="figures2/colorWheel.jpg"></center>
<center><span style="font-family: Helvetica,Arial,sans-serif;"> <p>Color wheel</p></span> </center>
<span style="font-family: Helvetica,Arial,sans-serif;"> <p>Color brewer is a good resource for color selection: <a href="http://colorbrewer2.org/">http://colorbrewer2.org/</a> </p></span>
<br>
<center><img style="width: 80%;" src="https://www.evl.uic.edu/aej/424/pics/week4/v2.jpg"></center><br>
<hr
style="width: 100%; height: 1px;">
Tables/images on this page are retrived from textbooks. Some were adapted from <a href="https://www.evl.uic.edu/aej/424/">Visualization and Visual Analytics class</a> at UIC by <a href="https://www.evl.uic.edu/aej/">Prof. Andrew Johnson</a>.
<div align="right"><font style="font-family:
Helvetica,Arial,sans-serif;" color="black" size="2">© Last revised: Feb 4th, 2019 </font></div>
</body>
</html>