https://github.com/lgatto/2017-05-03-rstatsintro-neu
Beginner's statistics in R
https://github.com/lgatto/2017-05-03-rstatsintro-neu
data introduction plotting r sample-size statistics t-test teaching-materials visualisation
Last synced: about 2 months ago
JSON representation
Beginner's statistics in R
- Host: GitHub
- URL: https://github.com/lgatto/2017-05-03-rstatsintro-neu
- Owner: lgatto
- Created: 2017-05-14T20:38:20.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2017-05-14T20:50:15.000Z (almost 8 years ago)
- Last Synced: 2025-01-20T22:55:03.524Z (3 months ago)
- Topics: data, introduction, plotting, r, sample-size, statistics, t-test, teaching-materials, visualisation
- Language: HTML
- Size: 59.2 MB
- Stars: 2
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Beginner's statistics in R
This course was set up and taught by Meena Choi and Laurent Gatto in
the frame the of the
[May Institute](http://computationalproteomics.ccis.northeastern.edu/programs/beginners-statistics-in-r/),
at the Northeastern University, Boston, MA from 3 to 5 May 2017. The
theoretical lectures were taught by Olga Vitek.
### Suggested reading
* [Points of Significance : Statistics for Biologists](https://www.nature.com/collections/qghhqm/pointsofsignificance)
### Schedule and material
[Material day 1](https://htmlpreview.github.io/?https://github.com/lgatto/2017-05-03-RstatsIntro-NEU/blob/master/01-rstats.html)
| Day | Time | Content |
|---------|---------------|---------------------|
| 3 May | 1:30 - 3:00pm | Keynote: Olga Vitek |
| | 3:00 - 3:30pm | Refreshments |
| | 3:30 - 5:00pm | R basics and RStudio|
| | 5:00 - 6:00pm | R markdown |
[Material day 2](https://htmlpreview.github.io/?https://github.com/lgatto/2017-05-03-RstatsIntro-NEU/blob/master/02-rstats.html)
| Day | Time | Content |
|---------|---------------|---------------------|
| 4 May | 8:00 - 9:00am | Bring your own data |
| | 9:00 - 10:30am| Data Exploration |
| | 10:30 - 11:00am| Refreshments |
| | 11:00 - 12:30pm| Visualisation |
| | 12:30 - 13:30pm| Lunch break |
| | 13:30 - 3:00pm | Lecture: basic stats |
| | 3:00 - 3:30pm | Refreshments |
| | 3:30 - 5:00pm | Basic stats, randomisation, error bars |
| | 5:00 - 6:00pm | Extra practice |
[Material day 3](https://htmlpreview.github.io/?https://github.com/lgatto/2017-05-03-RstatsIntro-NEU/blob/master/03-rstats.html)
| Day | Time | Content |
|---------|---------------|---------------------|
| 5 May | 8:00 - 9:00am | Bring your own data |
| | 9:00 - 10:30am| Lecture: sample size, linear regression, categorical data |
| | 10:30 - 11:00am| Refreshments |
| | 11:00 - 12:30pm| Statistical hypothesis testing |
| | 12:30 - 13:30pm| Lunch break |
| | 13:30 - 3:00pm | Sample size, categorical data hands-on |
| | 3:00 - 3:30pm | Refreshments |
| | 3:30 - 5:00pm | Linear models and correlation |
| | 5:00 - 6:00pm | Extra practice |
Lecture slides are available in the [Slides directory](https://github.com/lgatto/2017-05-03-RstatsIntro-NEU-/tree/master/Slides).
Link to [more teaching material](https://lgatto.github.io/TeachingMaterial/)
### License
This material, unless otherwise stated, has been adapted from our is
made available under the
[Creative Commons Attribution license](https://creativecommons.org/licenses/by/4.0/).
You are free to:
* **Share** - copy and redistribute the material in any medium or format
* **Adapt** - remix, transform, and build upon the material for any
purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
* **Attribution** - You must give appropriate credit, provide a link
to the license, and indicate if changes were made. You may do so in
any reasonable manner, but not in any way that suggests the licensor
endorses you or your use.
No additional restrictions - You may not apply legal terms or
technological measures that legally restrict others from doing
anything the license permits.
### Credit
Some of the material from day 1 and 2 has been adapted from the Data
Carpentry R lessons (see references in the respective sections), which
are licensed under CC-BY.