We have places available on the following online course:
Introductory Statistics for Life Scientists – Level 1
2nd October 2017 (for 5 weeks)
This is a 5 week course delivered entirely on-line within Learn (the University’s virtual learning environment, VLE). It will introduce students to the basic principles of statistical thinking (statistical inference) and one or two of the most common types of analysis that might be needed for Masters or PhD research projects. It is aimed mainly at students undertaking projects (at either level) in the College of Medicine & Veterinary Medicine (particularly in lab-based subjects), but it may be of more general use, too – we welcome participants from any discipline, although the examples used will tend to reflect the instructors’ backgrounds in clinical research, public health and veterinary medicine. The principles taught, however, are universal!
Each week, participants will use resources such as recorded PowerPoint presentations, quizzes, and directed reading to investigate a topic, and will try some practical examples in Minitab, a statistical package available on the University’s Managed Desktop and in general-access computing facilities. Support is available through discussion boards that allow queries on specific points, as well as more general interaction with the course team. The course runs asynchronously – participants work on course material and exercises in their own time, and interact via the discussion boards when required.
The following topics are covered in the 5 weeks:
- An introduction to the course and VLE
- Basic principles of statistical inference and exploratory data analysis
- Some basic concepts in probability
- Confidence intervals
- Hypothesis testing
Each topic is expected to take around 2.5 hours per week to complete. The full course should take around 12.5 hours.
The course runs for 5 weeks. A Level 2 course will run in the second half of Semester 1 and 2 to describe a number of additional topics and methods of analysis to enhance participants’ knowledge of, and confidence with, statistical methods.
List of Learning Outcomes. By the end of this workshop, students should be able to:
1. Describe and apply the basic principles of statistical inference and exploratory data analysis.
2. Identify and apply basic concepts in probability
3. Define and construct confidence intervals and be able to apply hypothesis testing appropriately
For more information and booking see: http://edin.ac/2dd5UOL
