By Jurisic A.
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Additional info for 1-Homogeneous Graphs with Cocktail Party, mu -Graphs
These statistical graphics can best be classiﬁed by the kind of data that they depict. Statistical data are usually characterized by their scale: nominal, ordinal (which are both categorical) or numerical (which is usually regarded as continuous). What is most important in distinguishing statistical graphics from other graphics is their universality: statistical graphics are not tailored towards only one speciﬁc application but are valid for any data measured on the appropriate scales. Depending on the data scale, certain standard graphing techniques have prevailed.
What he meant by “extensive” in 1966 is not recorded, but as an example he gives a dataset Healy reported on in 1952 with around 4,000 cases of 30 variables each. Ripley (2005) wrote in relation to car insurance proposals that the more questions potential customers are asked the less reliable their answers will become. ” In addition, the larger the dataset the more coding problems there are (varieties of missings, and coding variations in general, as the dataset will often have been compiled from different sources).
Therefore, all graphics of the book can be downloaded from the website as pdf-ﬁles for closer scrutiny (as long as no copyright applies). 2 Links to Software The book communicates principles, not details of speciﬁc implementations. Nevertheless, even the best considered principle needs an implementation in software and evaluation by users. 8 What Is on the Website 25 the ﬁgures that were directly drawn by that software (though in many cases other software could have been used just as well). 3 Datasets The index lists around 20 different datasets used in the book.
1-Homogeneous Graphs with Cocktail Party, mu -Graphs by Jurisic A.