Chemistry Core Statistics BeginnersPrerequisites
This course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. 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 or Python 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 open to students in the department of Chemistry
No prior programming experience is necessary.
Number of sessions: 8
# | Date | Time | Venue | Trainers | |
---|---|---|---|---|---|
1 | Wed 15 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
2 | Mon 20 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
3 | Wed 22 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
4 | Mon 27 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
5 | Wed 29 Jan 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
6 | Mon 3 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
7 | Wed 5 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
8 | Mon 10 Feb 2020 10:00 - 12:00 | 10:00 - 12:00 | Department of Chemistry | map | Matt Castle, Emer C. Jones |
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 eight 3 hour sessions held in the Department of Chemistry
Eight three hour sessions
Once a year
Booking / availability