Literature DB >> 17746394

Statistical data analysis in the computer age.

B Efron, R Tibshirani.   

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.

Year:  1991        PMID: 17746394     DOI: 10.1126/science.253.5018.390

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  134 in total

1.  Scan-rescan variation of measures derived from brain magnetization transfer ratio histograms obtained in healthy volunteers by use of a semi-interleaved magnetization transfer sequence.

Authors:  M Inglese; M A Horsfield; M Filippi
Journal:  AJNR Am J Neuroradiol       Date:  2001-04       Impact factor: 3.825

2.  Early widespread cortical distribution of coherent fusiform face selective activity.

Authors:  J Klopp; K Marinkovic; P Chauvel; V Nenov; E Halgren
Journal:  Hum Brain Mapp       Date:  2000-12       Impact factor: 5.038

3.  Scan statistics to scan markers for susceptibility genes.

Authors:  J Hoh; J Ott
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-15       Impact factor: 11.205

4.  Measuring tubulin content in Toxoplasma gondii: a comparison of laser-scanning confocal and wide-field fluorescence microscopy.

Authors:  Jason R Swedlow; Ke Hu; Paul D Andrews; David S Roos; John M Murray
Journal:  Proc Natl Acad Sci U S A       Date:  2002-02-05       Impact factor: 11.205

5.  Comparison of standard PCR/cloning to single genome sequencing for analysis of HIV-1 populations.

Authors:  Michael R Jordan; Mary Kearney; Sarah Palmer; Wei Shao; Frank Maldarelli; Eoin P Coakley; Colombe Chappey; Christine Wanke; John M Coffin
Journal:  J Virol Methods       Date:  2010-05-06       Impact factor: 2.014

6.  Significance and statistical errors in the analysis of DNA microarray data.

Authors:  James P Brody; Brian A Williams; Barbara J Wold; Stephen R Quake
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-16       Impact factor: 11.205

7.  A model-based approach for the analysis of neuronal information transmission in multi-input and -output systems.

Authors:  M Eger; R Eckhorn
Journal:  J Comput Neurosci       Date:  2002 May-Jun       Impact factor: 1.621

8.  Assessing the encoding of stimulus attributes with rapid sequences of stimulus events.

Authors:  M Eger; R Eckhorn
Journal:  J Comput Neurosci       Date:  2002 Nov-Dec       Impact factor: 1.621

Review 9.  Population genetics in the forensic DNA debate.

Authors:  B S Weir
Journal:  Proc Natl Acad Sci U S A       Date:  1992-12-15       Impact factor: 11.205

10.  Evidence that fast exocytosis can be predominantly mediated by vesicles not docked at active zones in frog saccular hair cells.

Authors:  Brian W Edmonds; Frederick D Gregory; Felix E Schweizer
Journal:  J Physiol       Date:  2004-08-12       Impact factor: 5.182

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