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Statistical Significance Tests for Machine Translation Evaluation
, 2004
"... If two translation systems differ differ in performance on a test set, can we trust that this indicates a difference in true system quality? To answer this question, we describe bootstrap resampling methods to compute statistical significance of test results, and validate them on the concrete exampl ..."
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Cited by 331 (2 self)
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If two translation systems differ differ in performance on a test set, can we trust that this indicates a difference in true system quality? To answer this question, we describe bootstrap resampling methods to compute statistical significance of test results, and validate them on the concrete
Discovering Statistically Significant Biclusters in Gene Expression Data
 In Proceedings of ISMB 2002
, 2002
"... In gene expression data, a bicluster is a subset of the genes exhibiting consistent patterns over a subset of the conditions. We propose a new method to detect significant biclusters in large expression datasets. Our approach is graph theoretic coupled with statistical modelling of the data. Under p ..."
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Cited by 302 (4 self)
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In gene expression data, a bicluster is a subset of the genes exhibiting consistent patterns over a subset of the conditions. We propose a new method to detect significant biclusters in large expression datasets. Our approach is graph theoretic coupled with statistical modelling of the data. Under
The case against statistical significance testing
 Harvard Educational Review
, 1978
"... In recent years the use of traditional statistical methods in educational research has increasingly come under attack. In this article, Ronald P Carver exposes the fantasies often entertained by researchers about the meaning of statistical significance. The author recommends abandoning all statistic ..."
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Cited by 151 (0 self)
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In recent years the use of traditional statistical methods in educational research has increasingly come under attack. In this article, Ronald P Carver exposes the fantasies often entertained by researchers about the meaning of statistical significance. The author recommends abandoning all
Statistical significance in psychological research
 Psychological Bulletin
, 1968
"... Most theories in the areas of personality, clinical, and social psychology predict no more than the direction of a correlation, group difference, or treatment effect. Since the null hypothesis is never strictly true, such predictions have about a SOSO chance of being confirmed by experiment when th ..."
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Cited by 108 (1 self)
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the theory in question is false, since the statistical significance of the result is a function of the sample size. Confirmation of a single directional prediction should usually add little to one's confidence in the theory being tested. Most theories should be tested by multiple corroboration and most
The insignificance of statistical significance testing.
 Journal of Wildlife Management,
, 1999
"... Abstract: Despite their wide use in scientific journals such as The Journal of Wildlife Management, statistical hypothesis tests add very little value to the products of research. Indeed, they frequently confuse the interpretation of data. This paper describes how statistical hypothesis tests are o ..."
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Cited by 92 (0 self)
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are often viewed, and then contrasts that interpretation with the correct one. I discuss the arbitrariness of Pvalues, conclusions that the null hypothesis is true, power analysis, and distinctions between statistical and biological significance. Statistical hypothesis testing, in which the null hypothesis
Statistical significance of communities in networks
 Physical Review E
"... Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multipurpose techniques, able to ha ..."
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Cited by 58 (2 self)
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and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions
On Statistical Significance of Signal *
, 812
"... Abstract A definition for the statistical significance of a signal in an experiment is proposed by establishing a correlation between the observed pvalue and the normal distribution integral probability, which is suitable for both counting experiment and continuous test statistics. The explicit exp ..."
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Abstract A definition for the statistical significance of a signal in an experiment is proposed by establishing a correlation between the observed pvalue and the normal distribution integral probability, which is suitable for both counting experiment and continuous test statistics. The explicit
Accurate Methods for the Statistics of Surprise and Coincidence
 COMPUTATIONAL LINGUISTICS
, 1993
"... Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used unjustifiably ..."
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Cited by 1057 (1 self)
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Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used
Statistical Significance of the Sequence Repeats
, 2003
"... The aim of this work is to approximate the distribution of the number of repeats in biological sequences modelled by Markov chains. Because of the inaccessibility of this distribution, we approximate it thanks to the ChenStein method using the poisson distribution. The goal of the application is to ..."
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is to find the statistical significance of the repeats in the genome of a biological species.
Thresholding of statistical maps in functional neuroimaging using the false discovery rate.
 NeuroImage
, 2002
"... Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a longstanding problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures for mult ..."
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Cited by 521 (9 self)
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controlling procedures will be effective for the analysis of neuroimaging data. These procedures operate simultaneously on all voxelwise test statistics to determine which tests should be considered statistically significant. The innovation of the procedures is that they control the expected proportion of the rejected
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