Key Information
Tutor: Dr John Pinney
Course Level: Level 1
Course Credit: 1 credit
Prerequisites: Familiarity with basic concepts of descriptive statistics
Course Duration: 3 hour session
Course Resources
Data analysis is a fundamental tool in quantitative research, but when faced with a big, messy dataset it can be difficult to know how to get started.
In this workshop, we will look at some basic techniques for getting data into a usable format and exploring it visually in order to formulate suitable questions and find the answers. We will also explore some of the principles behind good data visualisation practice when communicating results to others in reports or presentations.
The workshop will include a lot of hands-on practice using the Orange data science environment. No experience of programming is required.
Syllabus:
- What is exploratory data analysis?
- Getting data into a usable format
- Visualising distributions
- Dealing with outliers and missing values
- Exploring variation and covariation
- Graphics for communication
Learning Outcomes:
After completing this workshop, you will be better able to
- Format research data ready for analysis
- Formulate questions about a dataset
- Select a suitable visualisation for a given question
- Generate useful visualisations from your data
- Evaluate the effectiveness of a data visualisation
Dates & Booking Information
- Wednesday 08 January 2025, 14:00-17:00, Microsoft Teams
- Wednesday 16 April 2025, 10:00-13:00, South Kensington (In-Person Teaching)
To book your place, please follow the booking process advertised on the main programme page