Statistical Data Analysis in the Computer Age

by: Bradley Efron, Robert Tibshirani

Science, Vol. 253, No. 5018. (12 July 1991), pp. 390-395.

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Abstract

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. 10.1126/science.253.5018.390

@article{citeulike:1444801, abstract = {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. 10.1126/science.253.5018.390}, author = {Efron, Bradley and Tibshirani, Robert }, citeulike-article-id = {1444801}, doi = {http://dx.doi.org/10.1126/science.253.5018.390}, journal = {Science}, keywords = {bootstrap, review, statistics}, month = {July}, number = {5018}, pages = {390--395}, posted-at = {2007-07-09 21:10:18}, priority = {2}, title = {Statistical Data Analysis in the Computer Age}, url = {http://dx.doi.org/10.1126/science.253.5018.390}, volume = {253}, year = {1991} }

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TY - JOUR ID - citeulike:1444801 L3 - citeulike-article-id:1444801 TI - Statistical Data Analysis in the Computer Age JF - Science VL - 253 IS - 5018 SP - 390 EP - 395 N2 - 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. 10.1126/science.253.5018.390 KW - bootstrap KW - review KW - statistics AU - Efron, Bradley AU - Tibshirani, Robert PY - 1991/07/12/ UR - http://dx.doi.org/10.1126/science.253.5018.390 ER -

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