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  1. Using Bayes to get the most out of non-significant results.Zoltan Dienes - 2014 - Frontiers in Psychology 5:85883.
    No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors (...)
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  • The Role of Feedback in the Statistical Learning of Language‐Like Regularities.Felicity F. Frinsel, Fabio Trecca & Morten H. Christiansen - 2024 - Cognitive Science 48 (3):e13419.
    In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab‐based experiments, using artificial languages, many of the cues and features that are part of real‐world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language‐like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in (...)
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