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.

Intended Learning Outcomes (ILOs)

This module's assessment will evaluate your achievement of the ILOs listed here - you will see reference to these ILO numbers in the details of the assessment for this module.
On successfully completing the programme you will be able to:
Module-Specific Skills1. 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 Skills4. 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 Skills7. 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

Module Content

Syllabus Plan

Whilst the module’s precise content and order of syllabus coverage may vary, it is envisaged that it will include the following topics:

Introduction to R

Data management in R

Data Analysis in R

Linear Algebra

Sets and Functions

Probability

Optimisation

Web scraping and data retrieval with Python

Learning and Teaching

This table provides an overview of how your hours of study for this module are allocated:

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
201300

...and this table provides a more detailed breakdown of the hours allocated to various study activities:

CategoryHours of study timeDescription
Lectures with lab2010 x 2 hours of lectures and labs. These lectures cover the main concepts of the course. Sessions will sometimes include group and lab work.
Independent study130A variety of independent study tasks directed by module leader. These tasks may include (with an indicative number of hours): • Assigned readings (40 hours) • Preparation for and completion of practical assessments (60 hours) • Practicing techniques used in computer tutorials (30 hours)

Online Resources

This module has online resources available via ELE (the Exeter Learning Environment).

Maths Refresher Course (Gary King) http://projects.iq.harvard.edu/prefresher

UK Data Services - https://www.ukdataservice.ac.uk

NCRM - http://www.ncrm.ac.uk