 Lost Opportunities: Why We Need a Variety of Statistical LanguagesSanford Weisberg Journal of Statistical Software, 2004, vol. 013, issue i01 Abstract: To the worker who only has a hammer, we are told, everything looks like a nail. Solutions to applied statistical problems are framed by the limitations imposed by statistical computing packages and languages. For better or worse, we can do what the packages do; we cannot do what the packages won't do. Statistical languages like R have basic tools that allow the analyst to design new hammers, but even in R we cannot build an arbitrary hammer, only ones within the limits imposed by the R language. XLISP-STAT imposes different limitations, so we can produce different hammers. In this article, I look at some of the tools in XLISP-STAT that allow the user to think about graphics in ways that cannot be easily replicated in other statistical languages. The interactive graphical methods available in XLISP-STAT lead to very different methodology than would be developed without the tools that XLISP-STAT provides. The general approach to graphics and indeed to data analysis in general is quite different in a package like Arc that is built on top of XLISP-STAT, than it is in other statistical packages. We discuss why that might be true, and why this depends on design options created by XLISP-STAT. Date: 2004-12-20 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:013:i01 Access Statistics for this article Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis More articles in Journal of Statistical Software from Foundation for Open Access Statistics |
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