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Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses ...
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Feature overwriting as a finite mixture process: Evidence from comprehension data ...
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The statistical significance filter leads to overconfident expectations of replicability ...
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Statistical methods for linguistic research: Foundational Ideas - Part I ...
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Abstract:
We present the fundamental ideas underlying statistical hypothesis testing using the frequentist framework. We begin with a simple example that builds up the one-sample t-test from the beginning, explaining important concepts such as the sampling distribution of the sample mean, and the iid assumption. Then we examine the p-value in detail, and discuss several important misconceptions about what a p-value does and does not tell us. This leads to a discussion of Type I, II error and power, and Type S and M error. An important conclusion from this discussion is that one should aim to carry out appropriately powered studies. Next, we discuss two common issues we have encountered in psycholinguistics and linguistics: running experiments until significance is reached, and the "garden-of-forking-paths" problem discussed by Gelman and others, whereby the researcher attempts to find statistical significance by analyzing the data in different ways. The best way to use frequentist methods is to run appropriately ... : 30 pages, 9 figures, 3 tables. Under review with Language and Linguistics Compass. Comments and suggestions for improvement welcome. (Replaced version corrects several typos) ...
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Keyword:
Applications stat.AP; FOS Computer and information sciences; Methodology stat.ME
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URL: https://dx.doi.org/10.48550/arxiv.1601.01126 https://arxiv.org/abs/1601.01126
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Statistical methods for linguistic research: Foundational Ideas - Part II ...
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The cave of Shadows. Addressing the human factor with generalized additive mixed models ...
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