How to easily perform statistical analysis in Python with the Pengouin library

How to easily perform statistical analysis in Python with the Pengouin library

In this video, I will show you how you can use the Pingouin library to perform statistical analysis which you can use for your data science projects as well as research projects. Pingouin is an open-source statistical package available in Python. It is simple and yet provide exhaustive features.

In this video, I will show you how you can use the Pingouin library to perform statistical analysis which you can use for your data science projects as well as research projects. Pingouin is an open-source statistical package available in Python. It is simple and yet provide exhaustive features.

⭕ What can Pingouin do?

  1. ANOVAs: N-ways, repeated measures, mixed, ancova
  2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations
  3. Robust, partial, distance and repeated measures correlations
  4. Linear/logistic regression and mediation analysis
  5. Bayes Factors
  6. Multivariate tests
  7. Reliability and consistency
  8. Effect sizes and power analysis
  9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient
  10. Circular statistics
  11. Chi-squared tests

⭕ Links for this video:

Code https://github.com/dataprofessor/ping...

Pingouin website https://pingouin-stats.org/

⭕ Install Pingouin:

pip install pingouin

or

conda install -c conda-forge pingouin

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