Using the R language for statistics

R language is unusual and in some ways it isn't actually just a language that defines what is going on. In this case there are interfaces, archives, built-ins, and many other things associated. Like perl, it has an archive called cran which has code and modules in the same way as perl. In some ways the language is dependent on what can be done with the language, how easy to learn and apply, as well as maintain and extend. I prefer Python for ease of use, but like cpan, there are things that can only be appreciated when considered in context.

data(faithful) attach(faithful) names(faithful) hist(eruptions, seq(1.6, 5.2, 0.2), prob=T) lines(density(eruptions, bw=0.1)) rug(eruptions,seide=1)

These two examples are R used inside zim wiki and so it is just the scripts , which can be run at an interactive R console also. There is a flavor that represents the context and sometimes it is difficult to appreciate some perspectives without diving into the ocean of knowledge and data to see what is down under the surface.

Weight<-c(1,2,3,4,5) boxplot(Weight) boxplot(Weight, horizontal=T) rug(Weight, side=2)


Automated Intelligence

Automated Intelligence
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