A Handbook of Statistical Graphics Using SAS ODS by Geoff Der, Brian S. Everitt

By Geoff Der, Brian S. Everitt

Easily Use SAS to supply Your Graphics

Diagrams, plots, and different kinds of snap shots are essential elements in approximately all stages of statistical research, from the preliminary review of the knowledge to the choice of applicable statistical versions to the prognosis of the selected types when they were suited to the knowledge. Harnessing the complete portraits services of SAS, A instruction manual of Statistical images utilizing SAS ODS covers crucial graphical tools wanted in each statistician’s toolkit. It explains the way to enforce the tools utilizing SAS 9.4.

The guide indicates how one can use SAS to create many varieties of statistical portraits for exploring info and diagnosing geared up types. It makes use of SAS’s more moderen ODS photographs all through as the program deals a number of benefits, together with ease of use, prime quality of effects, constant visual appeal, and handy semiautomatic graphs from the statistical strategies.

Each bankruptcy offers graphically with a number of units of instance facts from a large choice of components, corresponding to epidemiology, drugs, and psychology. those examples illustrate using image monitors to offer an summary of knowledge, to signify attainable hypotheses for trying out new info, and to interpret outfitted statistical types. The SAS courses and knowledge units can be found online.

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G. imagename='Figure 2'. 2 ODS Styles Whereas the ODS destination determines the general format of the output, its appearance in terms of fonts, colours and other attributes depends on the ODS style in use. There are a number of built-in styles and each output destination has a default style optimized for that destination. The default style for html is called htmlblue and those for the listing and rtf destinations are called listing and rtf, respectively. The names of other built-in styles can be listed by submitting: proc template; list styles; run; Where the final output is to be in black and white, with greyscale fills or ­shading, the journal style is a good choice.

Here graphics for displaying the distribution of forearm lengths are required. 3 are the survival times (in days) for patients suffering from gastric cancer, that is, the time from diagnosis until death. dat. Again displaying the distribution of the survival times graphically is the aim. Geyser eruptions—For the final example in this chapter we will consider some data collected on the Old Faithful geyser. Geysers are natural fountains that shoot up into the air, at more or less regular intervals, a column of heated water and steam.

Been severely criticized. Tufte (1983), for example, comments that ‘tables are preferable to graphics for many small datasets. A table is nearly always better than a dumb pie chart; the only worse design than a pie chart is several of them …. pie charts should never be used’. A similar lack of affection is shown by Bertin (1981), who declares that ‘pie charts are completely useless’, and by Wainer (1997) who claims that ‘pie charts are the least useful of all graphical forms’. e. one where the ‘dots’ are arranged in order of the corresponding rates.

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