June 14, 2009
June 14, 2009
June 17, 2009
Computers in Education
14.912.1 - 14.912.11
Non-Parametric, Computer-Intensive Statistics: A Primer
The authors have developed a first course in statistics for engineers based on non- parametric, computer-intensive (NPCI) statistical methods. These methods do not rely on calculus or knowledge of statistical distribution theory, and as such can be taught earlier in a curriculum, are more intuitive, are less-recipe driven, and can be retained longer than traditional parametric statistics. In this paper, we provide a primer on NPCI methods. Basic NPCI concepts of bootstrapping and permutation are described. These concepts are then applied to confidence interval construction and hypothesis testing. Several examples taken from the course are worked to elucidate the methods.
The authors have developed a new type of entry level statistics course focused on non-parametric computer-intensive (NPCI) statistics. NPCI methods do not rely on calculus because they do not depend on assumed distribution functions (thus non-parametric), instead their theory relies heavily on simple sampling concepts and their implementation utilizes computer re-sampling (thus computer- intensive). As a first course in statistics, NPCI methods are more useful for many students than traditional statistics because the basic theory posits that sampling from a sample of observed data mimics sampling from a conceptual (or real) population.
The potential benefits of a NPCI course are threefold. First, the course can be taught earlier in a curriculum than traditional statistics. Second, the methods are more intuitive and therefore stay with students longer. Finally, more sophisticated statistical procedures can be taught and used. These benefits mean that students are better equipped to solve statistical problems later in their careers. The benefits of NPCI are being investigated and results are presented elsewhere. This paper focuses on the concepts, methods, and applications of NPCI statistics.
The theory behind many NPCI methods is not new. Many of the basic concepts have been in the statistics literature since the 1940’s. However, NPCI methods
McDonald, T., & Mukai, D. (2009, June), Nonparametric, Computer Intensive Statistics: A Primer Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--5027
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