HS52012: Mathematics and programming skills for social scientists
[Page last updated: 15 August 2024]
Academic Year: | 2024/25 |
Owning Department/School: | Faculty of Humanities & Social Sciences (units for MRes programmes) |
Credits: | 5 [equivalent to 10 CATS credits] |
Notional Study Hours: | 100 |
Level: | Masters UG & PG (FHEQ level 7) |
Period: |
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Assessment Summary: | CWRI 100% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: | |
Learning Outcomes: |
* Acquisition of skills in specific data analysis methods and tools (for example, multi-level modelling); * Proficiency in the use of relevant computer packages/languages (MLwiN, R, Python); * Proficiency in using data from large scale surveys; * Ability to be able to manipulate and construct new data sets from secondary data sources; * Ability to select the appropriate analytical technique and associated computer program (and language) for the analysis required for a given research question; * Ability to use 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. |
Synopsis: | Gain the advanced-level mathematical skills needed to overcome various types of optimisation problems.
You'll learn to use software that can solve practical optimisation problems within research. |
Content: | This course is delivered via three full-day sessions, plus pre-reading delivered online in advance of each full-day session. Additional computer lab sessions also take place within 'home' institutions to prepare the coursework. The main topics covered are programming statistical and graphical techniques using R; dynamic programming and coding using Python; multi-level modelling theory and application using MLwiN. Each day-long session will involve lectures outlining the theory behind a technique or the rudiments of a programming language, its application and use, along with practical sessions implementing the skills learned on a common dataset that will be used for each of the three day-long sessions and with each of the different computing packages. |
Course availability: |
HS52012 is a Must Pass Unit on the following courses:Department of Education
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Notes:
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