MRC Core Statistics Beginners
This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.
There are three core goals for this course:
- Use R confidently for statistics and data analysis
- Be able to analyse datasets using standard statistical techniques
- Know which tests are and are not appropriate
R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.
In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory
After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.
- The course is a bespoke course targeted specifically at students enrolled on the MRC DTP
No previous statistical knowledge assumed.
Number of sessions: 6
| # | Date | Time | Venue | Trainer | |
|---|---|---|---|---|---|
| 1 | Tue 21 Jan 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
| 2 | Thu 23 Jan 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
| 3 | Tue 28 Jan 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
| 4 | Thu 30 Jan 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
| 5 | Tue 4 Feb 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
| 6 | Thu 6 Feb 2020 14:00 - 17:00 | 14:00 - 17:00 | Clinical School, E-learning 1, 2, 3 (Level 2) | map | Matt Castle |
Learning Objectives After this course you should be able to:
- Analyse datasets using standard statistical techniques
- Know when each test is and is not appropriate
During this course you will learn about:
- One and two sample hypothesis tests
- ANOVA
- Simple linear Regression
- ANCOVA
- Linear Models
- Model selection techniques
- Power analyses
The course is primarily based around computer practicals interspersed with short lectures and presentations used to explain core ideas and principles.
The course is split over six 3 hour sessions all held in the eLearning Suite within the Clinical School. If you book onto this course you must attend all of the sessions as detailed below.
Six three hour sessions
Once per year
Booking / availability