Data Analysis and Visualization using Bootstrap-Coupled Estimation.
Estimation statistics is a simple framework <https://thenewstatistics.com/itns/> that—while avoiding the pitfalls of significance testing—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 significance testing.
An estimation plot has two key features. Firstly, it presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. Secondly, an estimation plot presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes.
Please cite this work as: Moving beyond P values: Everyday data analysis with estimation plots Joses Ho, Tayfun Tumkaya, Sameer Aryal, Hyungwon Choi, Adam Claridge-Chang https://doi.org/10.1101/377978
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for dabest-2023.2.14-py2.py3-none-any.whl