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BUSI41J15: MODELLING AND ANALYSIS FOR MANAGEMENT (FT)

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 4
Credits 15
Availability Not available in 2024/2025
Module Cap
Location Durham
Department Management and Marketing

Prerequisites

  • None.

Corequisites

  • None.

Excluded Combinations of Modules

  • None.

Aims

  • To provide students with a sufficiently detailed knowledge of methods for solving quantitative problems to permit them to appreciate material covered elsewhere in the MBA programme.

Content

  • Data description.
  • The Normal distribution.
  • Inference: means, proportions, contingency tables (Chi-squared).
  • Applications of statistical models to management problems, e.g. risk and monitoring.
  • Linear models: simple regression and applications; introduction to linear programming.

Learning Outcomes

Subject-specific Knowledge:

  • By the end of this module, students should have a detailed knowledge of key concepts in data description and statistical modelling; monitoring and hypothesis testing; and linear models.

Subject-specific Skills:

  • By the end of this module, students should:
  • Be able to use a range of standard statistical tests and apply them to complex management problems;
  • Be able to use modelling applications within Excel and apply them to complex management problems.

Key Skills:

  • Written communication.
  • Planning, organising and time management.
  • Problem solving and analysis.
  • Using initiative.
  • Computer literacy.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Learning outcomes will be met through a combination of lectures, groupwork, case studies, practical (computer) classes and discussion, supported by guided reading. The summative assessment, by written assignment, will test students' understanding of and ability to apply relevant analytical techniques.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Workshops (a combination of lectures, groupwork, case studies, practical (computer) classes and discussion)28Yes
Preparation and Reading122 
Total150 

Summative Assessment

Component: Written AssignmentComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Written Assignment4,000 words maximum100 

Formative Assessment

Weekly quantitative exercises.

More information

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