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Data Manipulation & Management (Module)

Module description

This module aims to provide students with the data manipulation skills to work with complex hierarchical and panel data sets in the social sciences.

Aims:

  • Understand how complex social science large scale datasets are structured and the implications of this;
  • Be able to prepare complex social science datasets for appropriate statistical analysis by:
      • Being able to manipulate, recode and compute variables using syntax files and understand how missing data can be dealt with.
      • Learning how to combine multiple datasets, and aggregate and disaggregate data from different files in a relational database.
      • Learning complex computation of derived variables.
  • Have practical experience of the manipulation of large, complex datasets to answer questions of importance in the context of health and social research.

As prerequisites to registering on this module, Master students must have completed the Quantitative Data Analysis module (7SSHM504).

There is no reading for this course, apart from the detailed workbooks which students will be supplied with each day.

Staff information

Dr Jennifer Dowd

Teaching pattern

The module is taught in one week during term three. Each day of the week, the module will begin with a lecture, and then the class will move to a computer lab where tutors will be available to assist students as they complete a self-completion workbook.

 

Module assessment - more information

4 x completed workbooks (25%) 
1 x 2,500 word research assignment (75%)

Key information

Module code 7SSHM507

Credit level 7

Assessment coursework

Credit value 15

Semester summer session 1

Study abroad module No