Module POLM030 for 2019/0
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
POLM030: Mathematics and Programming Skills for Policy Analytics
This module descriptor refers to the 2019/0 academic year.
Module Aims
The module will cover basic maths and programming skills that you will require to progress on the MSc in Policy Analytics. The main aims of the module are:
- Develop basic maths skills for data analysis
- Develop proficiency in the use of relevant computer packages/languages (R, Python);
- Introduce you to Application Programming Interfaces (APIs) of various web sources (such as Twitter) to obtain large amounts of data allowing understanding of the scope of possibilities that are open to a researcher without special “big data” resources.
- Develop skills in managing large scale structured and unstructured data and constructing new databases from different sources;
- Develop skills in using the R package for data analysis.
On successfully completing the programme you will be able to: | |
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Module-Specific Skills | 1. Demonstrate proficiency in the use of specific programming languages/packages used for statistical analysis: e.g. R and Python. 2. Understand code in R and implement appropriate commands to perform relevant statistical analyses (topics covered will include types of variables, functions and parameters, conditional commands and constructs such as when and for cycles). 3. Use Application Programming Interfaces to obtain data for potential use in future research projects (Python). |
Discipline-Specific Skills | 4. Developed computer programming skills in a way that results in high level of synergies with quantitative research skills. 5. Manipulate data in each program and use the appropriate in-built analytic tools. 6. Interpret output from each program and draw appropriate inference regarding the hypotheses being tested. |
Personal and Key Skills | 7. Demonstrate understanding of and use a full range of computing skills effectively and independently 8. Demonstrate understanding of and use a full range of data management skills effectively and independently |
Indicative Reading List
This reading list is indicative - i.e. it provides an idea of texts that may be useful to you on this module, but it is not considered to be a confirmed or compulsory reading list for this module.
Basic reading:
Cioffi-Revilla, Claudio. Introduction to computational social science: principles and applications. Springer Science & Business Media, 2013.
Gill, Jeff. 2006. Essential Mathematics for Political and Social Research. Cambridge, England: Cambridge University Press.
Bush, ROBERT R., et al. "Mathematics for social scientists." The American Mathematical Monthly 61.8 (1954): 550-561.
Kropko, Jonathan. Mathematics for Social Scientists. SAGE Publications, 2015.