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Unification of Statistical Methods for Continuous and Discrete Data

In: Computing Science and Statistics

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  • Emanuel Parzen

    (Texas A&M University, Department of Statistics)

Abstract

We propose the concept of unification of statistical methods in order to develop a general philosophy of statistical data analysis. We propose that ways of thinking about statistical ends (goals) and means (procedures) are needed that provide a framework for implementing and comparing several different approaches to a data analysis problem. We believe that unification has benefits which include: existing (often parametric) methods will be better understood; many new (often nonparametric) methods will be developed. The new methods are usually computer intensive; consequently unification of statistical methods can be considered to be closely related to computational statistics. We define computational statistical methods as characterized by being graphics intensive and number crunching intensive.

Suggested Citation

  • Emanuel Parzen, 1992. "Unification of Statistical Methods for Continuous and Discrete Data," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 235-242, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_30
    DOI: 10.1007/978-1-4612-2856-1_30
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