Installation
About
Data Analysis using Bootstrap-Coupled 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, 1548-7105. doi:10.1038/s41592-019-0470-3. The free-to-view PDF is located at
Citation | dabestr citation info |
github.com/ACCLAB/dabestr | |
acclab.github.io/dabestr/ |
Key Metrics
Downloads
Yesterday | 16 0% |
Last 7 days | 88 -35% |
Last 30 days | 509 -12% |
Last 90 days | 1.798 -7% |
Last 365 days | 6.445 -3% |