SOCIAL DATA ANALYTICS - 2022/3
Module code: SOCM064
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice during the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
BRUNTON-SMITH Ian (Sociology)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: G300
Module cap (Maximum number of students): N/A
Overall student workload
Workshop Hours: 20
Independent Learning Hours: 105
Guided Learning: 15
Captured Content: 10
|Assessment type||Unit of assessment||Weighting|
|Coursework||Data analysis descriptive exercise (1500 words)||30|
|Coursework||Data analysis regression exercise (2500 words)||70|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: SOCM064
Programmes this module appears in
|Criminology MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Criminology (Corporate Crime and Corporate Responsibility) MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Criminology (Cybercrime and Cybersecurity) MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.