QUANTITATIVE METHODS II - 2020/1
Module code: MAND031
In light of the Covid-19 pandemic, and in a departure from previous academic years and previously published information, the University has had to change the delivery (and in some cases the content) of its programmes, together with certain University services and facilities for the academic year 2020/21.
These changes include the implementation of a hybrid teaching approach during 2020/21. Detailed information on all changes is available at: https://www.surrey.ac.uk/coronavirus/course-changes. This webpage sets out information relating to general University changes, and will also direct you to consider additional specific information relating to your chosen programme.
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This unit builds on the Quantitative Methods I unit in semester 1. Students are exposed to (more) advanced methodological and statistical skills needed to understand and evaluate journal articles that use quantitative methods. This also enables students to have a basic understanding of the different methods, so they are able to choose the appropriate method needed for their research questions. Methods discussed include: logistic regressions, Poisson regression, log linear models, instrumental variables, multilevel analysis, longitudinal data analysis (time series and panel data) and other advanced techniques such as bayesian techniques, cluster analysis and social network analysis.
Surrey Business School
MASSARO Sebastiano (SBS)
Number of Credits: 0
ECTS Credits: 0
Framework: FHEQ Level 8
JACs code: N300
Module cap (Maximum number of students): N/A
Prerequisites / Co-requisites
Generalized Linear Models.
Generalized Linear Models: Logit Models.
Generalized Linear Models: Poisson Models.
Simple Panel Data Methods.
Advanced Panel Data Methods.
Instrumental Variables. Two Stage Least Squares.
Mediation and Moderation.
Advanced Statistical techniques (Bayesian, SNA, Clustering, Deep Learning)
|Assessment type||Unit of assessment||Weighting|
|Coursework||ASSESSMENT (AS.1)-EMPIRICAL RESEARCH PROJECT||Pass/Fail|
The assessment strategy is designed to provide students with the opportunity to demonstrate their learning and achievement of the unit’s learning outcomes. Both the formative and summative assessments enable the achievement of the learning outcomes. The regular class participation and feedback enhance students’ learning and support their preparation and delivery of the two elements of summative assessment. These are outlined below.
Formative assessment will comprise an ongoing feature of this unit. Students will actively engage in taught sessions and prepare for these via guided readings, discussion topics and other preparatory work issued by the instructor. These will be important for students and will facilitate their critical thinking and applied skills development, as well as enhance their learning and preparation for the three summative assessment elements.
The summative assessment for this unit consists of:
- Assessment 1. Empirical research project.
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Overall student workload
Methods of Teaching / Learning
The learning and teaching strategy is designed to support and achieve the learning outcomes. The learning and teaching methods include class contact sessions which are highly interactive in nature, class discussion, preparatory reading, verbal student presentations, student-led reviews of readings, practical activities, scenario discussion, and individual written assignments.
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.
Reading list for QUANTITATIVE METHODS II : http://aspire.surrey.ac.uk/modules/mand031
Programmes this module appears in
|Management and Business PHD||2||Optional||Each unit of assessment must be passed at 50% 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 2020/1 academic year.