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[Review]: High-dimensional Statistics #19
Comments
Thank you for submitting this lesson for review, @gperu. My capacity for managing lesson reviews is quite limited at the moment and I will not be able to handle reviews of all of your submitted lessons simultaneously. If you have a preference for which lesson(s) you would like us to prioritise for review, please let me know and I will do my best to focus on that/those first. |
Thanks @tobyhodges and @gperu. Probably good to keep this course towards the end. @hannesbecher and I are working on some final changes to incorporate some of the feedback we have received during delivery. I will add a note here when ready. |
@gperu could you please add @hannesbecher as an author? I can't edit the issue. |
Hi @tobyhodges and @gperu. @hannesbecher and I completed our last round of planned changes so these materials are now ready to be reviewed. Please let me know what do we need to do to get the process started. Best |
Note that I cannot edit the original post in this thread to add additional authors or suggest reviewers |
Hi @tobyhodges, following further community reviews and changes, we would like to re-submit the lesson for review if at all possible. We totally understand that your capacity for reviews is limited. In case this helps, we have documented our community reviews, changes made in response to these reviews, and how we conform to The Carpentries' requirements here. |
Editor checks on-going 🤚 Editor Checklist - High-dimensional StatisticsAccessibility
Content
Design
RepositoryThe lesson repository includes:
Structure
Supporting informationThe lesson includes:
General
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Lesson Title
High-dimensional Statistics with R
Lesson Repository URL
https://github.com/carpentries-incubator/high-dimensional-stats-r
Lesson Website URL
https://carpentries-incubator.github.io/high-dimensional-stats-r/
Lesson Description
This course is intended for those who have a working knowledge of statistics and linear models with R and wish to learn high-dimensional statistical methods with R.
This is a short course aimed at familiarising learners with statistical and computational methods for the extremely high-dimensional data commonly found in biomedical and health sciences (e.g., gene expression, DNA methylation, health records). These datasets can be challenging to approach, as they often contain many more features than observations, and it can be difficult to distinguish meaningful patterns from natural underlying variability. To this end, we will introduce and explain a range of methods and approaches to disentangle these patterns from natural variability. After completion of this course, learners will be able to understand, apply, and critically analyse a broad range of statistical methods. In particular, we focus on providing a strong grounding in high-dimensional regression, dimensionality reduction, and clustering.
Author Usernames
@alanocallaghan
@catavallejos
@ailithewing
Zenodo DOI
No response
Differences From Existing Lessons
No response
Confirmation of Lesson Requirements
JOSE Submission Requirements
paper.md
andpaper.bib
files as described in the JOSE submission guide for learning modulesPotential Reviewers
No response
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