This module is not offered.

Aims

The aims of this module are:

  • To introduce students to the types, properties, and problems of real data
  • To provide to students the principles, knowledge and tools to address the complexities and workflows of answering questions from data
  • To introduce students to the principles and methods of creating visual representations of data
  • To enable students to carry out a full data analysis process, from information gathering through to decision support

Learning Outcomes

On successful completion of this module, the student should:

  • Be able to gather and prepare data for analysis
  • Be able to carry out and understand simple statistical analyses of data
  • Be able to carry out sensemaking and exploratory analysis sessions on data
  • Be able to formulate precise questions that are answerable through data analysis
  • Be able to use and develop visual tools to explore, verify and communicate data insights

Syllabus

  • Introduction to the visual analytics process
  • Data collection and preparation
  • Statistics for Data
  • Sensemaking and analysis processes
  • Visualisation techniques
  • Specialised visualisation techniques for specific types of data

Compulsory Elements

This module has the following compulsory elements in addition to those common to all modules (mark of 4 in each assessment component):

  • Carry out the weekly readings
  • Attend tutorial sessions
  • Participate in project presentations

Module Delivery

  • [Adriana Wilde][5]

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Last Published: 02 Apr 2024.