Approach to Statistical Significance Testing
Which Cities Produce More Excellent Papers Than Can Be Expected? A New Mapping Approach, Using Google Maps, Based on Statistical Significance Testing
... our approach is more analytically oriented by allowing the assessment of an observed number of excellent papers for a city against the expected ...this approach can not only identify the top performers in ...
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The Role of Statistical Significance Testing In Educational Research
... of statistical testing is important in terms of how methods of statistical analysis have developed in the recent ...of statistical analysis approaches (including ANOVA methods) relies on ...
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The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing
... BLEU (Papineni et al., 2002), ROUGE (Lin, 2004), METEOR (Banerjee and Lavie, 2005), UAS and LAS (K¨ubler et al., 2009), are unique measures that were developed for NLP applica- tions. BLEU and METEOR are standard evalu- ...
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BRIEF REPORTS Advances in Testing the Statistical Significance of Mediation Effects
... lacks statistical power relative to methods that attempt to correct for this ...steps approach, their simulation analyses suggested that the NT method lacks statistical power relative to other alter- ...
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Testing the significance of calendar effects
... The third difference between our approach and STW is the choice of statistical test. The hypothesis that there are no calendar specific anomalies is a two-sided hypothesis of multiple equalities. Our test ...
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Significance Testing for Allelic Heterogeneity
... test; statistical power; GWAS; conditional/joint modeling T HERE has been growing interest in detecting causal var- iants in fine mapping for a disease or complex trait of interest, which can tell us about the ...
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An Empirical Investigation of Statistical Significance in NLP
... simple approach to approximating the response of these factors for tasks where large numbers of sys- tem outputs are not ...tistical significance is complex, and therefore sim- ple thresholds are not a ...
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A Tutorial on Hunting Statistical Significance by Chasing N.
... There is increasing concern about the replicability of studies in psychology and cognitive neuroscience. Hidden data dredging (also called p-hacking) is a major contributor to this crisis because it substantially ...
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A Tutorial on Hunting Statistical Significance by Chasing N
... There is increasing concern about the replicability of studies in psychology and cognitive neuroscience. Hidden data dredging (also called p-hacking) is a major contributor to this crisis because it substantially ...
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Visualizing statistical significance of disease clusters using cartograms
... the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing ...for statistical significance of a ...
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The Use of Meta-Analytic Statistical Significance Testing
... hypothesis testing by correcting for all possible statistical tests in a given ...of statistical tests based on the rows of Table ...the statistical significance of the mean effect ...
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A sample size planning approach that considers both statistical significance and clinical significance
... The results of our method indicate that sample size needs to be increased but our intention is not to mandate larger sample sizes per se. Such an effort may be futile since in practice cost constraints force clinical ...
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Statistical Significance Testing and Cumulative Knowledge in Psychology: Implications for Training of Researchers
... The belief that such studies are worthless is based on two false assumptions: (a) the assumption that each individual study must be able to support and justify a conclusion, and (b) the [r] ...
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Abandon statistical significance
... improved statistical methods that move beyond NHST and include multilevel modeling, machine learning, sta- tistical graphics, and other tools for analyzing and visualizing large amounts of data; applied examples ...
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statistical significance estimation
... standard approach, or using entropy-weighting to yield lower information content models), against three different databases of 10 5 random sequences, of lengths L = 100, 400, and 1600, collecting multihit local ...
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Clinical Significance: A Statistical Approach to Defining Meaningful Change in Psychotherapy Research
... Ftgure 4 The same approximations of dysfunctional and functional distributions for Global Distress Scale of the Marital Satisfaction In- ventory with reference to three suggeste[r] ...
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What statistical significance means
... What Statistical Significance Means Siu ...neither statistical significance nor effect size is indicative of the replicability of research ...that significance tests have no role to ...
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STATISTICAL SIGNIFICANCE OF RANKING PARADOXES
... a statistical perspective, however, there is no significant difference between the candidates in any case, and the weakening of one candidate does not change ...of statistical significance should be ...
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Introduction. Hypothesis Testing. Hypothesis Testing. Significance Testing
... Formulating a hypothesis test Interpreting a hypothesis test Common types of hypothesis test Power calculations Hypothesis tests and confidence intervals.. Hypothesis Testing.[r] ...
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The meaning of significance in data testing
... while non-significant results will often be negligible—thus, misinterpretation (2) is not so, but a correct interpretation. Under Neyman-Pearson’s approach, on the other hand, effect sizes are those of ...
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