Undergraduate Module Descriptor
SOC2094: Data Analysis in Social Science III
This module descriptor refers to the 2018/9 academic year.
|Term(s) and duration|
This module ran during term 2 (11 weeks)
Dr Alexey Bessudnov (Lecturer)
POL/SOC1041 and POL/SOC2077
POL/SOC2077 if not taken before
|Available via distance learning|
Basic knowledge of statistics and data analysis is often not enough for dealing with more complicated problems in the social sciences, as well as in market research, applied policy analysis, and data-driven journalism. This module introduces you to more advanced techniques for social data analysis using the statistical programming language R and in particular the tidyverse framework. These techniques are especially useful while working with large longitudinal data sets. While some statistical theory is covered in this module, the discussion of statistical concepts is generally non-mathematical and intuitive and is based on numerous examples from social sciences. The module assumes familiarity with basic descriptive statistics and linear regression analysis.
POL/SOC1041 and POL/SOC2077 are the pre-requisites for this module.