Visualization of Categorical Data Review

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(More customer reviews)Having read a lot of conference proceedings in my time I would say this is better than most. Don't read this if you want a coherent view of data visualisation. It's a mixture of cutting edge stuff, work in progress, reports on what has worked in practice, plus a couple that were probably written as their employer won't send them to a conference unless they present *something*. As I said, a typical conference mixture. Usually I'm delighted if more than 5% of the papers are of interest. The yield is about 20%. I am interested in what works in practice for the statistical illiterate user in a survey environment. So I look for data visualisation in terms of putting statistical understanding in the graph without the user knowing. So for me some of the papers are useful, but if you're interested in some other aspect, well, you'll be interested in other papers. I must admit some of the papers had me thinking they're stretching the title of this. Michael Friendly's paper was interesting as usual, though not much not already out there (see recent JASA?). The Billiet et al paper I found particularly useful. I have found biplots are a useful, if rather underutilised method. Ditto for the Gabriel paper. Blasius paper is raising interesting ideas, and I feel it should feed into cognitive testing. A bit of a fan of CART, so the Lausen paper was interesting, though I always assumed CART was an EDA technique, rather than an end in itself. the Whittaker paper gave me some food for thought. The Windmoller, Voges & Francis papers were interesting to me, even given their rather subject-matter foci. I find how someone analyses data is sometimes useful, even if I'm not working in that field, as was the case here. Summary: Can't say I'd personally buy it, but would recommend any decent technical library to buy.

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A unique and timely monograph, Visualization of Categorical Data contains a useful balance of theoretical and practical material on this important new area. Top researchers in the field present the books four main topics: visualization, correspondence analysis, biplots and multidimensional scaling, and contingency table models.This volume discusses how surveys, which are employed in many different research areas, generate categorical data. It will be of great interest to anyone involved in collecting or analyzing categorical data. * Correspondence Analysis* Homogeneity Analysis* Loglinear and Association Models* Latent Class Analysis* Multidimensional Scaling* Cluster Analysis* Ideal Point Discriminant Analysis* CHAID* Formal Concept Analysis* Graphical Models

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