May Institute 2019: Beginner’s statistics in R
2019-05-02
Before we start
- Download the data files here: https://lgatto.github.io/MayInstituteRstatsIntro/RIntro.zip
- A pdf version of the course is available here: https://lgatto.github.io/MayInstituteRstatsIntro/RIntro.pdf
- An pre-installed cloud-based RStudio session is available here: https://rstudio.cloud/project/332801
Suggested reading
Schedule
| Day | Time | Content |
|---|---|---|
| 1 | 1:30 - 3:00pm | Lecture: Introduction to statistics (OV) |
| 3:00 - 3:30pm | Refreshments | |
| 3:30 - 5:00pm | R basics and RStudio (LG) | |
| 5:00 - 6:00pm | R markdown (LG) | |
| 2 | 8:00 - 9:00am | Q&A |
| 9:00 - 10:30am | Data Exploration (LG) | |
| 10:30 - 11:00am | Refreshments | |
| 11:00 - 12:30pm | Data Exploration 2 (LG) | |
| 12:30 - 13:30pm | Lunch break | |
| 13:30 - 3:00pm | Lecture: Statistical inference (OV) | |
| 3:00 - 3:30pm | Refreshments | |
| 3:30 - 5:00pm | Visualisation (LG) | |
| 5:00 - 6:00pm | Extra practice | |
| 3 | 8:00 - 9:00am | Q&A |
| 9:00 - 10:30am | Randomisation, summaries, error bars and confidence intervals (MC) | |
| 10:30 - 11:00am | Refreshments | |
| 11:00 - 12:30pm | Lecture: sample size, linear regression, categorical data (OV) | |
| 12:30 - 13:30pm | Lunch break | |
| 13:30 - 2:15pm | Linear models and correlation (LG) | |
| 2:15 - 3:00pm | Introduction to MSnbase (LG) |
|
| 3:00 - 3:30pm | Refreshments | |
| 3:30 - 5:00pm | Hypothesis testing and categorical data and samples size calculation (MC) | |
| 5:00 - 6:00pm | Wrap-up |
Olga Vitek (OV), Meena Choi (MC), Laurent Gatto (LG)
License
This material, unless otherwise stated, is made available under the Creative Commons Attribution license.
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 also licensed under CC-BY.