Purposes and strategies in regression analysis

Data analysis remains a subject of practice and informal teaching. In the 1980s, there were several attempts to identify ingredients of a theory of data analysis, in which John Tukey took an active part. A theme within this unexplored field of statistical science consists of formalizing strategies f...

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Bibliographic Details
Published in:Journal of statistical planning and inference 2004-05, Vol.122 (1), p.175-186
Main Author: Stahel, Werner A
Format: Article
Language:English
Subjects:
Exact sciences and technology
Exploratory data analysis
Linear inference, regression
Mathematics
Model building
Multivariate analysis
Practice of data analysis
Probability and statistics
Sciences and techniques of general use
Statistics
Strategies for data analysis
Theory of data analysis
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Summary:Data analysis remains a subject of practice and informal teaching. In the 1980s, there were several attempts to identify ingredients of a theory of data analysis, in which John Tukey took an active part. A theme within this unexplored field of statistical science consists of formalizing strategies for specified tasks. Such strategies can be used—in addition to training—for writing smart statistical procedures and programs for guided analysis. Furthermore, different strategies might be compared as to their success, as soon as there are evaluation criteria for the results. Defining such criteria is yet another aspect of the theory of data analysis. Focus here is on sketching a strategy for multiple linear regression as a starting point. 1 1 This paper is dedicated to John Tukey who gave his comments to an early version 18 years ago.
ISSN:0378-3758
1873-1171
DOI:10.1016/j.jspi.2003.06.018