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data_sanitation.html
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<!DOCTYPE html>
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<head>
<meta charset="utf-8" />
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<title>Data sanitation</title>
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<h1 class="title toc-ignore">Data sanitation</h1>
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<div id="TOC">
<ul>
<li><a href="#quality-assessment">Quality assessment</a></li>
<li><a href="#mitigating-missingness">Mitigating missingness</a></li>
<li><a href="#imputation">Imputation</a></li>
<li><a href="#logarithmic-transformation">Logarithmic transformation</a></li>
<li><a href="#scaling-and-centering">Scaling and centering</a></li>
<li><a href="#references">References</a></li>
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<div id="quality-assessment" class="section level2">
<h2>Quality assessment</h2>
<p>When we are presented with a dataset a first question is ‘what is the quality of this data?’. Or perhaps more eloquently stated, ‘garbage in, roses out’ <span class="citation">(Tabachnick, Fidell, and Osterlind 2001)</span>? A first task associated with any data analysis is to assess the quality of the data.</p>
</div>
<div id="mitigating-missingness" class="section level2">
<h2>Mitigating missingness</h2>
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<div id="imputation" class="section level2">
<h2>Imputation</h2>
</div>
<div id="logarithmic-transformation" class="section level2">
<h2>Logarithmic transformation</h2>
</div>
<div id="scaling-and-centering" class="section level2">
<h2>Scaling and centering</h2>
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<div id="references" class="section level1 unnumbered">
<h1>References</h1>
<div id="refs" class="references">
<div id="ref-tabachnick2001using">
<p>Tabachnick, Barbara G, Linda S Fidell, and Steven J Osterlind. 2001. “Using Multivariate Statistics.” Allyn; Bacon Boston.</p>
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<p>Copyright © Brian J. Knaus. All rights reserved.</p>
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