Undergraduate Module Descriptor

SSIM905: Mathematics and Programming Skills for Social Scientists

This module descriptor refers to the 2021/2 academic year.

Module Aims

The module aims to introduce you to basic maths and programming skills that you require to progress on the MRes in AQM. The topics covered include:

    • Basic maths skills for data analysis
    • Proficiency in the use of relevant computer packages/languages (MLwiN, R, Python);
    • Managing data from large scale surveys and constructing new databases from different sources;
    • Ability to be able to manipulate and construct new data sets from secondary data sources;
    • 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.

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 three specific programming languages/packages used for statistical analysis: R, Python and MLwiN.
2. Understand code in each language 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 APIs to obtain data for potential use in future research projects.
Discipline-Specific Skills4. Developed coding skills suitable for conducting high-level complex quantitative analyses.
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 computing skills
8. Demonstrate understanding of data management skills

How this Module is Assessed

In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.

Formative Assessment

A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
3 x Problem set of questions (one after each full day session)3 short exercises/questions each1-7Oral

Summative Assessment

A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.

CourseworkWritten examsPractical exams
10000

...and this table provides further details on the summative assessments for this module.

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
One 2750 word research project using the skills/techniques developed in one of the programming languages/applications to investigate a research problem relevant to the student’s chosen discipline.1002750 words1-8Written Feedback
0
0
0
0
0

Re-assessment

Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Research projectResearch project1-8August/September reassessment period