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Entries clarify key concepts such as adjusted principal inertias, biplots and their vectors/axes, scaling and normalization choices, and core methods like correspondence analysis, canonical correspondence analysis, and classical scaling. It also defines mathematical tools and measures including chi-square distance, contribution to variance/inertia, centroids, bootstrapping, and matrix constructs.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/biplots-in-practice-appendix-c-glossary-of-terms/290017/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/biplots-in-practice-appendix-c-glossary-of-terms/290017.png","ImageObject",300,407,{"name":92,"@type":93},"wps_ap_test_251126_0180","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-10","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",16,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the purpose of Appendix C in this book?","Question",{"text":113,"@type":114},"Appendix C contains an alphabetical list of the most common terms used in the book, along with short definitions for each term.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How does the glossary define a biplot?",{"text":118,"@type":114},"A biplot is defined as a joint display of points representing rows and columns of a table, where the scalar product between a row point and a column point approximates the corresponding table element in an optimal way.",{"name":120,"@type":111,"acceptedAnswer":121},"What does “chi-square distance” mean here?",{"text":122,"@type":114},"Chi-square distance is a weighted Euclidean distance between profiles, where each squared difference is divided by the corresponding element of the average profile; it is the distance function used in correspondence analysis.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290017,1789639919,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144,"preview_page_count":4},8796095027276,"https://avatar.qwps.com/avatar/d3BzX2FwX3Rlc3RfMjUxMTI2XzAxODA=","Biplots in Practice  \nMICHAEL GREENACRE  \nProfessor of Statistics at the Pompeu Fabra University  \nAppendix C Offprint  \nGlossary of Terms  \nFirst published: September 2010  \nISBN: 978-84-923846-8-6  \nSupporting websites: [http://www.fbbva.es](http://www.fbbva.es)[ ](http://www.fbbva.es)[http://www.multivariatestatistics.org](http://www.multivariatestatistics.org)  \n© Michael Greenacre, 2010  \n© Fundación BBVA, 2010  \nAPPENDIX  \nGlossary of Terms  \nIn this appendix an alphabetical list of the most common terms used in this book is given, along with a short definition of each. Words in italics refer to terms which are contained in the glossary.  \n— adjusted principal inertias: a modification of the results of a multiple correspondence analysis that gives a more accurate and realistic estimate of the inertia accounted for in the solution.  \n— aspect ratio: the ratio between a unit length on the horizontal axis and a unit length on the vertical axis in a graphical representation; should be equal to 1 for any biplot or map that has a spatial interpretation.  \n— asymmetric biplot/map: a joint display of the rows and columns where the two clouds of points have different scalings (also called normalizations), usually one in principal coordinates and the other in standard coordinates.  \n— biplot: a joint display of points representing the rows and columns of a table such that the scalar product between a row point and a column point approximates the corresponding element in the table in some optimal way.  \n— biplot axis: a line in the direction of a biplot vector onto which points can be projected in order to estimate values in the table being analysed.  \n— biplot vector: a vector drawn from the origin to a point in a biplot, often representing a variable of the data matrix, or a supplementary variable.  \n— bootstrapping: a computer-based method of investigating the variability of a statistic, by generating a large number of replicate samples, with replacement, from the observed sample.  \n— Burt matrix: a particular matrix of concatenated tables, consisting of all two-way cross-tabulations of a set of categorical variables, including the cross-tabulations of each variable with itself.  \n— calibration: the process of putting a scale on a biplot axis with specific tic-marks and values.  \nC  \n205  \nBIPLOTS IN PRACTICE  \n— canonical correspondence analysis (CCA): extension of correspondence analysis to include external explanatory variables; the solution is constrained to have dimensions that are linearly related to these explanatory variables.  \n— centroid: weighted average point.  \n— chi-square distance: weighted Euclidean distance measure between profiles, where each squared difference between profile elements is divided by the corresponding element of the average profile; the distance function used in correspondence analysis.  \n— classical scaling: a version of multidimensional scaling which situates a set of points in multidimensional Euclidean space, based on their interpoint distances or dissimilarities, and then projects them down onto a low-dimensional space of representation.  \n— concatenated table: a number of tables, usually based on cross-tabulating the same individuals, joined together row-wise or column-wise or both.  \n— contingency table: a cross-tabulation of a set of cases or objects according to two categorical variables; hence the grand total of the table is the number of cases.  \n— contribution to variance/inertia: component of variance (or inertia) accounted for by a particular point on a particular principal axis; these are usually expressed relative to the corresponding principal variance (or principal inertia) on the axis (giving a diagnostic of how the axis is constructed) or relative to the variance (or inertia) of the point (giving a measure of how well the point is explained by the axis).  \n— contribution (or standard) biplot: biplot in which one set of points, usually the variables, is normalized so that thei","cbCaikpA92rUYUxR","https://ap.wps.com/l/cbCaikpA92rUYUxR","pdf",87192,"English","# Appendix C Offprint\n## Glossary of Terms (Alphabetical)\n## Key Definitions and Measures\n## Biplot and Correspondence Analysis Concepts","[{\"question\":\"What is the purpose of Appendix C in this book?\",\"answer\":\"Appendix C contains an alphabetical list of the most common terms used in the book, along with short definitions for each term.\"},{\"question\":\"How does the glossary define a biplot?\",\"answer\":\"A biplot is defined as a joint display of points representing rows and columns of a table, where the scalar product between a row point and a column point approximates the corresponding table element in an optimal way.\"},{\"question\":\"What does “chi-square distance” mean here?\",\"answer\":\"Chi-square distance is a weighted Euclidean distance between profiles, where each squared difference is divided by the corresponding element of the average profile; it is the distance function used in correspondence analysis.\"}]","Biplots in Practice - Appendix C - Glossary of Terms | PDF",25]