Data literacy – understanding data

Learn how to select, understand and use data in reports, presentations, recommendations and evidence-based policy.

Course topics

Defining data

  • What do we mean by data?
  • What types of data might we encounter and where do we find it?

Key statistics

  • Measures of central tendency (mean, median, mode) and when to use them
  • Percentages, rates, ratios, probabilities
  • Significance, error, correlation and causation

Describing your data

  • Language of evidence, risk and causation
  • Biased language
  • Writing recommendations

Accessible and open data

  • Open and closed data
  • Big data and data licensing

Learning outcomes

By the end of this course, participants should be able to:

  • recognise the need for data skills
  • recognise types of data and types of variables
  • interpret key statistics
  • recognise biased, loaded and imprecise language when used to describe data
  • find and evaluate data, including its licensing
  • recognise the difference between studies and evidence.

Learning method

This interactive course includes lectures, group discussions, exercises and comprehensive course notes.