This module provides an introduction to the basics of data analysis, exploration and visualisation, with particular focus on spatial and temporal data. The module consists of a series of lectures including an introduction and start-up session to a take away practical exercise using the statistical programming language R. The module begins with basic methods to explore, describe and graphically represent one- and two-dimensional data, before moving on to consider more advanced methods to manipulate and visualise geographical information, and explore and identify trends and seasonal patterns in time series data. In addition, some methodological aspects of data analysis are introduced, in particular the use of open data and ‘citizen science’ data and the idea of reproducibility in data analysis.
Outcome:
On successful completion of the module, students should be able to:
Demonstrate basic proficiency in coding and data analysis using R, in particular
Understand the basics of time series modelling
Understand the basics of spatial trend modeling
Perform interactive graphical exploration of spatial and temporal data
Create interactive web maps, time series visualisations and reports
Demonstrate awareness of the need for critical evaluation of data used in the above.
