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<h1 class="center">Outliers</h1>
<div class="words"><p>
&quot;Outliers&quot; are values that &quot;<b>lie</b> <b>out</b>side&quot; the other values. </div>
<p style="float:right; margin: 0 0 5px 10px;"><img src="images/outlier.svg" alt="outlier" /></p>
<p>When we collect data, sometimes there are values that are &quot;far away&quot; from the main group of data ... what do we do with them?</p>
<div style="clear:both"></div>
<p>&nbsp;</p>
<div class="example">
<h3>Example: Long Jump</h3>
<p style="float:left; margin: 0 10px 5px 0;"><img src="images/long-jump.jpg" width="150" height="114" alt="long jump" /></p>
<p>A new coach has been working with the Long Jump team this month, and the athletes' performance has changed. </p>
<p>Augustus can now jump 0.15m further, June and Carol can jump 0.06m further. </p>
<p>Here are all the results:</p>
<ul>
<li>Augustus: +0.15m</li>
<li>Tom: +0.11m</li>
<li>June: +0.06m</li>
<li>Carol: +0.06m </li>
<li>Bob: + 0.12m</li>
<li>Sam: -0.56m</li>
</ul>
<p>Oh no! Sam got worse.</p>
<p>Here are the results on the number line:</p>
<p class="center"><img src="images/outlier-example1.svg" style="max-width:100%" alt="outlier example 1" /></p>
<p>The <b><a href="../mean.html">mean</a></b> is: </p>
<p class="center">(0.15+0.11+0.06+0.06+0.12-0.56) / 6 = -0.06 / 6 = <b>-0.01m</b></p>
<p>So, on average the performance went <b>DOWN</b>. </p>
<p class="center"><b>The coach is obviously useless ... right?</b></p>
</div>
<p>Sam's result is an &quot;Outlier&quot; ... what if we remove Sam's result?</p>
<p class="center"><img src="images/out-liar.svg" style="max-width:100%" alt="out, liar!" /></p>
<div class="example">
<h3>Example: Long Jump (continued)</h3>
<p>Let us try the results WITHOUT Sam:</p>
<p class="center"><img src="images/outlier-example1a.svg" style="max-width:100%" alt="outlier example without outlier" /></p>
<p class="center">Mean = (0.15+0.11+0.06+0.06+0.12)/5 = <b>0.1 m</b></p>
<p>Hey, the coach looks much better now!</p>
</div>
<p>But is that fair? Can we just get rid of values we don't like?</p>
<h2>What To Do? </h2>
<p class="center larger">You need to think &quot;why is that value over there?&quot; </p>
<p>It may be quite normal to have high or low values</p>
<ul>
<li>People can be short or tall</li>
<li>Some days there is no rain, other days there can be a downpour</li>
<li>Athletes can perform better or worse on different days</li>
</ul>
<p>Or there may be an unusual reason for extreme data</p>
<div class="example">
<h3>Example: Long Jump (continued)</h3>
<p>We find out that Sam was feeling sick that day. Not the coach's fault at all.</p>
<p>So it is a good idea <b>in this case</b> to remove Sam's result. </p>
</div>
<p>When we remove outliers we are <b>changing the data</b>, it is no longer &quot;pure&quot;, so we shouldn't just get rid of the outliers without a good reason!</p>
<p>And when we do get rid of them, we should <b>explain what we are doing and why</b>.</p>
<h2>Mean, Median and Mode</h2>
<p>We saw how outliers affect the <a href="../mean.html">mean</a>, but what about the <a href="../median.html">median</a> or <a href="../mode.html">mode</a>?</p>
<div class="example">
<h3>Example: Long Jump (continued)</h3>
<p>The median (&quot;middle&quot; value):</p>
<ul>
<li>including Sam is: 0.085</li>
<li>without Sam is: 0.11 (went up a little)</li>
</ul>
<p>The mode (the most common value):</p>
<ul>
<li>including Sam is: 0.06</li>
<li>without Sam is: 0.06 (stayed the same) </li>
</ul>
<p>The mode and median didn't change very much.</p>
<p>They also stayed around where most of the data is. </p>
</div>
<p>So it seems that outliers have the biggest effect on the mean, and not so much on the median or mode.</p>
<p>Hint: calculate the median and mode when you have outliers. </p>
<p>You can also try the <a href="../numbers/geometric-mean.html">Geometric Mean</a> and <a href="../numbers/harmonic-mean.html">Harmonic Mean</a>.</p>
<p>&nbsp;</p>
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