Data Analysis using BootstrapCoupled ESTimation. Estimation statistics is a simple framework that avoids the pitfalls of significance testing. It uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one's experiment/intervention, as opposed to a false dichotomy engendered by P values. An estimation plot has two key features: 1. It presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. 2. It presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes. Estimation plots are introduced in Ho et al., Nature Methods 2019, 15487105. <doi:10.1038/s4159201904703>. The freetoview PDF is located at <https://rdcu.be/bHhJ4>.
Package details 


Author  Joses W. Ho [cre, aut], Tayfun Tumkaya [aut] 
Maintainer  Joses W. Ho <joseshowh@gmail.com> 
License  file LICENSE 
Version  0.3.0 
URL  https://github.com/ACCLAB/dabestr 
Package repository  View on CRAN 
Installation 
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