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  "Description": "Data Analysis using Bootstrap-Coupled ESTimation.\nEstimation statistics is a simple framework that avoids the\npitfalls of significance testing. It uses familiar statistical\nconcepts: means, mean differences, and error bars. More\nimportantly, it focuses on the effect size of one's\nexperiment/intervention, as opposed to a false dichotomy\nengendered by P values.  An estimation plot has two key\nfeatures: 1. It presents all datapoints as a swarmplot, which\norders each point to display the underlying distribution.  2.\nIt presents the effect size as a bootstrap 95% confidence\ninterval on a separate but aligned axes.  Estimation plots are\nintroduced in Ho et al., Nature Methods 2019, 1548-7105.\n<doi:10.1038/s41592-019-0470-3>.  The free-to-view PDF is\nlocated at\n<https://www.nature.com/articles/s41592-019-0470-3.epdf?author_access_token=Euy6APITxsYA3huBKOFBvNRgN0jAjWel9jnR3ZoTv0Pr6zJiJ3AA5aH4989gOJS_dajtNr1Wt17D0fh-t4GFcvqwMYN03qb8C33na_UrCUcGrt-Z0J9aPL6TPSbOxIC-pbHWKUDo2XsUOr3hQmlRew%3D%3D>.",
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