Description
This course provides a refresher on the foundations of statistical analysis. The emphasis is on interpreting the results of a statistical test, and being able to determine the correct test to apply.
Practicals are conducted using a series of online apps, and we will not teach a particular statistical analysis package, such as R.
Target audience
Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
Please be aware that these courses are only free for University of Cambridge students. All other participants e.g Staff will be charged a registration fee in some form.
Prerequisites
No previous experience required
Sessions
1-day course
Topics covered
Bioinformatics, Data handling, Statistical calculation
Objectives
After this course you should be able to:
- State the assumptions required for a one-sample and two-sample t-test and be able to interpret the results of such a test
- Know when to apply a paired or independent two-sample t-test
- Assess the distribution of your data and decide if a parametric or non-parametric test is required
- Perform simple statistical calculations using the online app
- Understand the limitations of the tests taught within the course
- Know when more complex statistical methods are required
Aims
During this course you will learn about:
- Different types of data, distributions and structure within data
- Summary statistics for continuous and discrete data
- Formulating a null hypothesis
- Assumptions of one-sample and two-sample t-tests
- Interpreting the result of a statistical test
- Statistical tests of categorical variables
- Non-parametric versions of one- and two-sample tests
Format
Presentations and practicals