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MN50588: Quantitative methods for management (accounting & finance)

[Page last updated: 15 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: School of Management
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 100%
Further information on unit assessment Assessment Detail:
  • Coursework (CW 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites: Before taking this module you must take MN50554 or equivalent.
Description: Aims:
This is an intermediate/advanced course on statistical analysis for postgraduate students. The aim of the course is to provide students with a critical understanding of the strengths and weaknesses of statistical analysis alongside a detailed knowledge of particular statistical techniques. By the end, the unit will equip students with the skills to contribute to research projects. This course equips students with a sufficient knowledge of STATA that they can competently analyze data and estimate different types of models. The emphasis of the course is on the practical issues relating to data analysis and modelling rather than econometric theory.

Learning Outcomes:
Knowledge and understanding
* Understand the basic principles of statistical analysis
Intellectual skills
* Appreciate the strengths and weakness of statistical inquiry
* Be able to use, model and interpret correlation, linear multiple regression analyses
* Be able to use one or more of a range of advanced statistical techniques including:
* Univariate analysis (Manipulating datasets, descriptive statistics)
* Ordinary least squares regression analysis (and diagnostics)
* Non-linear regressions (logit, multinomial models, ordered models, Poisson, tobit)
* Cox proportional hazards models
* Panel data,
* Endogeneity instrumental variables, and self-selection.
* Be able to use STATA to carry out statistical analysis
Professional practical skills
* Acquire computing skills.

Skills:

* Appropriate use of quantitative research methods and analysis techniques (T, F, A)
* Appreciate the strengths and weaknesses of different quantitative methods (T, F, A)
* Use of STATA in conducting t-tests, ANOVAs and Regressions
* Be able to define a researchable problem and formulate research questions and hypotheses (T, F, A)
* Understand the role of sampling and the concepts of generalisability, validity and reliability (T, F, A)
* Be able to conduct basic tests for scale validity and reliability in STATA (T, F, A)
* Understand the next step in validity and reliability testing (T, F, A)
* Select appropriate statistical tests (T, F, A)
Professional practice skills
* Understand ethical issues in relation to quantitative research (T, F, A)
* Acquire computing skills (T, F, A).

Content:
The approach taken will be essentially practical and a critical appreciation of the analytical techniques mentioned above will be based around a number of realistic datasets.
Further information on programme availabilityProgramme availability:

MN50588 is Optional on the following programmes:

School of Management

Notes:

  • This unit catalogue is applicable for the 2020/21 academic year only. Students continuing their studies into 2021/22 and beyond should not assume that this unit will be available in future years in the format displayed here for 2020/21.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.