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<div class="calibre2"><span class="calibre7"><span class="calibre8">Consensus on the original data, i.e. no standardization is performed, is a plain PCA analysis
comprising scores, loadings, correlation and explained variances for the first two principal
components (PC).</span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"></span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8">The PC number to be used may be changed by clicking the buttons with arrows on the
figures. The maximum number of PCs calculated depends on how many samples or
attributes the data set contains. The lowest number of any of the two will be the number of
PCs calculated.</span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"><br class="calibre10"/></span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"><br class="calibre10"/></span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"><br class="calibre10"/></span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"><b class="calibre14">Further reading:</b></span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8">Risvik E. & Naes T., <i class="calibre13">Multivariate Analysis of Data in Sensory Science,</i> 1996 (Elsevier
Science).</span></span></div><div class="calibre2"><span class="calibre7"><span class="calibre8"><br class="calibre10"/></span></span></div><div class="calibre2"> </div>
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