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11#
發(fā)表于 2025-3-23 09:54:09 | 只看該作者
12#
發(fā)表于 2025-3-23 15:11:18 | 只看該作者
Further Useful Graphics,ormative method for drawing such a comparison. By using a univariate or bivariate scaling of multivariate data however, a . plot can also be used for comparing two multivariate samples with each other. The univariate and multivariate cases will now be discussed.
13#
發(fā)表于 2025-3-23 20:42:53 | 只看該作者
14#
發(fā)表于 2025-3-23 22:50:44 | 只看該作者
https://doi.org/10.1007/978-3-662-53229-4ta in two dimensions. Some of these techniques, such as Andrews’ curves and Chernoff faces, have captured the imagination of the research community (particularly the non-statisticians) and are currently enjoying widespread interest. Some ten representations will be discussed in this chapter and illu
15#
發(fā)表于 2025-3-24 05:32:20 | 只看該作者
https://doi.org/10.1007/978-94-009-5946-0s between them, are difficult to determine merely by looking at the matrix. However, if the above information can be simplified to representations in one, two or three dimensions at the most, the human eye is usually capable of observing any differences and interactions between rows and columns with
16#
發(fā)表于 2025-3-24 08:59:13 | 只看該作者
Macmillan Motor Vehicle Engineering Seriesrmulating any structural relationships between the variables. The computer programs CHAID and XAID, which are to be discussed in this chapter, are both examples of so-called AID procedures (Automatic Interaction Detection), according to which the outcome of a dependent variable . can be predicted on
17#
發(fā)表于 2025-3-24 13:38:29 | 只看該作者
18#
發(fā)表于 2025-3-24 14:57:54 | 只看該作者
19#
發(fā)表于 2025-3-24 23:02:34 | 只看該作者
Graphical Exploratory Data Analysis978-1-4612-4950-4Series ISSN 1431-875X Series E-ISSN 2197-4136
20#
發(fā)表于 2025-3-25 00:11:47 | 只看該作者
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