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

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

There are no further sessions taking place this academic year. Course dates for 2024-25 will be available to book from late September.

To book your place, please follow the booking process advertised on the main programme page