Skip to main content

Data Analysis and Visualization using Bootstrap-Coupled Estimation.

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dabest-0.1.5.tar.gz (21.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dabest-0.1.5-py2.py3-none-any.whl (22.1 kB view details)

Uploaded Python 2Python 3

File details

Details for the file dabest-0.1.5.tar.gz.

File metadata

  • Download URL: dabest-0.1.5.tar.gz
  • Upload date:
  • Size: 21.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.4

File hashes

Hashes for dabest-0.1.5.tar.gz
Algorithm Hash digest
SHA256 21b4ad57ee495579b08d77a43aa66fa35aa78ca83d800f90ef5446735636ae83
MD5 fdccd1687cf7c8ea38b1d11e3793b04c
BLAKE2b-256 9c9753ea464e053a51897a14754d5fe223d1a2b7a992d39b7a8220ae43830464

See more details on using hashes here.

File details

Details for the file dabest-0.1.5-py2.py3-none-any.whl.

File metadata

  • Download URL: dabest-0.1.5-py2.py3-none-any.whl
  • Upload date:
  • Size: 22.1 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.4

File hashes

Hashes for dabest-0.1.5-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 a036c2df40d383bf0e690ea8f997fcdad870bd88995c4c71763545137a89375e
MD5 8ff20d4d7dda9f2d2bbbad8c17b1d38a
BLAKE2b-256 c48e92755603c5217e7760a9943aea1050cb83e78f23e9e89ed0f41ca6d1afc1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page