https://github.com/stephaneguerrier/data-analytics
Data analytics class for Pharmaceutical Sciences graduate students at U. Geneva.
https://github.com/stephaneguerrier/data-analytics
course data-analytics r statistics
Last synced: over 1 year ago
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Data analytics class for Pharmaceutical Sciences graduate students at U. Geneva.
- Host: GitHub
- URL: https://github.com/stephaneguerrier/data-analytics
- Owner: stephaneguerrier
- Created: 2021-02-20T11:51:18.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2025-02-27T22:20:16.000Z (over 1 year ago)
- Last Synced: 2025-02-28T07:14:12.038Z (over 1 year ago)
- Topics: course, data-analytics, r, statistics
- Language: HTML
- Homepage:
- Size: 93.7 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
---
output: github_document
---
Welcome to the course **Data Analytics for Pharmaceutical Sciences**. These documents were prepared by [Stéphane Guerrier](https://stephaneguerrier.com/), [Dominique-Laurent Couturier](https://github.com/dlc48), Wenfei Chu and [Yuming Zhang](https://github.com/Yuming-Zhang).
# Course materials
The linked slides (below) are `.html` files that will only work properly if you are connected to the internet. If you're going off grid, grab the PDFs. You'll miss out on gifs and videos, but the rest will still show up.
*Note:* The slides were created with [`xaringan`](https://github.com/yihui/xaringan/wiki) in [R](cran.r-project.org) and the [template](https://github.com/edrubin/EC607S20) is based on the work of [Ed Rubin](https://edrub.in)
**[Part I: Introduction to Statistical Inference](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture1.html)** (note formats: [.html](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture1.html) | [.pdf](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture1.pdf) | [.Rmd](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture1.Rmd))
**[Part II: Analysis of Variance](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture2.html#1)** (note formats: [.html](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture2.html#1) | [.pdf](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture2.pdf) | [.Rmd](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture2.Rmd))
**[Part III: Linear Regression](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture3.html#1)** (note formats: [.html](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture3.html) | [.pdf](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture3.pdf) | [.Rmd](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture3.Rmd))
**[Part IV: Generalized Linear Models](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture4.html)** (note formats: [.html](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture4.html) | [.pdf](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture4.pdf) | [.Rmd](https://raw.githack.com/stephaneguerrier/data_analytics/master/Lecture4.Rmd))
**Part V: Generalized Additive Model** (coming soon 🚧)
# License
[CC BY NC SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)