FOUNDATIONS OF STATISTICS AND ECONOMETRICS - 2022/3
Module code: MANM467
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 in time for the start of 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.
This module is an introduction to the methods of specification, estimation and testing of statistical and econometric models. The techniques are applied to business data making use of the statistical computer packages (e.g. Stata).
Surrey Business School
TAVALAEI Mahdi (SBS)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: N200
Module cap (Maximum number of students): 100
Overall student workload
Independent Learning Hours: 97
Tutorial Hours: 11
Laboratory Hours: 11
Guided Learning: 20
Captured Content: 11
Prerequisites / Co-requisites
Review of descriptive statistics and statistical inference (e.g., estimation, hypotheses testing, etc.); Analysis of variance; Linear Regression basics, and OLS model; Multiple regression using cross sectional and panel data; Regression diagnostics (e.g., multicollinarity, serial correlation and heteroskedasticity); Endogeneity, causal inference, instrumental variables, and two-stage least squares (2SLS) regression; Supplementary topics (e.g., difference in difference method, nonlinear regressions, etc.)
|Assessment type||Unit of assessment||Weighting|
|Coursework||STATISTICAL COMPUTER PACKAGE||100|
Coursework exercise which can be completed off-campus.
This module has a technical and a practical component. The latter is, at this level, more important. As such, assessment emphasises work based on applying theoretical knowledge using econometric and statistical package (mainly Stata) in the form of an off-class project, in which students are asked to analyse real economic data. The technical component is assessed via a written examination. Thus, the summative assessment for this module consists of: • 40% In-semester test: written exam about the probability and statistics and simple regressions. • 60% a final written report of applying econometric analyses on a real world dataset using computer package. Formative assessment and feedback is done by a Feedback section in Surreylearn, plus specific, individualised written comments, feedback meetings with students and general feedback in classes.
- Provide knowledge of fundamental concepts and models widely used in statistical and econometric analyses
- Apply theoretical concepts and use their understanding and insight gained throughout the unit to implement and interpret econometric models
- Use various types of quantitative data to make decisions in the business world
|001||Display a fundamental understanding of the statistical and econometric analysis (such as assumptions, inference, and diagnostics),||KC|
|002||Be able to build econometric models and analyse various types of quantitative data, and interpret the results,||KPT|
|003||Be able to evaluate empirical research in the field of business critically, and propose and apply robustness tests, and||KCPT|
|004||Be able to write up a full-fledged econometric analysis report on real-world data, and to communicate clearly and evaluate the findings critically.||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to: give students the theoretical (and practical) tools they need to analyse real world situations; encourage rigour in their approach to problems; encourage hands-on study of empirical problems; The learning and teaching methods include: readings using lecturers, solving exercises, responding to questions in class, preparing and taking part in the test.
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: MANM467
This module has a capped number and may not be available to ERASMUS and other international exchange students. Please check with the International Engagement Office email: firstname.lastname@example.org
Programmes this module appears in
|Business Analytics 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.