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Science 12 July 1991:
Vol. 253. no. 5018, pp. 390 - 395
DOI: 10.1126/science.253.5018.390

Articles

Statistical Data Analysis in the Computer Age

BRADLEY EFRON 1 and ROBERT TIBSHIRANI 2

1 Department of Statistics, Stanford University, Stanford, CA 94305
2 Department of Preventive Medicine and Biostatistics and Department of Statistics, University of Toronto, Ontario, Canada M5S 1A8

Most of our familiar statistical methods, such as hypothesis testing, linear regression, analysis of variance, and maximum likelihood estimation, were designed to be implemented on mechanical calculators. Modern electronic computation has encouraged a host of new statistical methods that require fewer distributional assumptions than their predecessors and can be applied to more complicated statistical estimators. These methods allow the scientist to explore and describe data and draw valid statistical inferences without the usual concerns for mathematical tractability. This is possible because traditional methods of mathematical analysis are replaced by specially constructed computer algorithms. Mathematics has not disappeared from statistical theory. It is the main method for deciding which algorithms are correct and efficient tools for automating statistical inference.


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