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

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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
12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation, etc.
⭕ Links for this video:
⭕ Install Pingouin:
pip install pingouin
or
conda install -c conda-forge pingouin
⭕ Playlist:
Check out our other videos in the following playlists.
⭕ Recommended Books:
⭕ Stock photos, graphics and videos used on this channel:
⭕ Follow us:
⭕ Disclaimer:
Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents.
#pingouin #statistics #statisticalanalysis #datascience #dataanalyst #analytics #machinelearning #dataprofessor #bigdata #machinelearning #datamining #bigdata #ai #artificialintelligence #dataanalytics #dataanalysis #dataprofessor
⭕ 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
12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation, etc.
⭕ Links for this video:
⭕ Install Pingouin:
pip install pingouin
or
conda install -c conda-forge pingouin
⭕ Playlist:
Check out our other videos in the following playlists.
⭕ Recommended Books:
⭕ Stock photos, graphics and videos used on this channel:
⭕ Follow us:
⭕ Disclaimer:
Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents.
#pingouin #statistics #statisticalanalysis #datascience #dataanalyst #analytics #machinelearning #dataprofessor #bigdata #machinelearning #datamining #bigdata #ai #artificialintelligence #dataanalytics #dataanalysis #dataprofessor
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