Quantitative Methods

Module overview

MANG6003 aims to develop statistical reasoning. Via a series of examples and activities, students are introduced to the idea of probability modelling and how it can be applied to aid decision making in uncertain situations, which are frequently encountered in organisations. On successful completion of this module, students should be able to collect relevant data and summarise the main features of an uncertain situation, to identify standard problems and analyse them with the correct statistical tools, to process and analyse data in a statistical computer package, to understand the risks involved in a decision which involves uncertainty, and quantify such risks. Students should also develop problem solving skills, modelling skills, become familiar with a standard statistical computer package (SPSS), and be able to interpret and critically evaluate statistical results.

Aims and Objectives

Learning Outcomes

Transferable and Generic Skills

Having successfully completed this module you will be able to:

develop technical, analytical, critical thinking and presentational skills;
process, analyse and display data in a statistical computer package (SPSS);
work effectively in a team.
collect relevant data and summarise the main features of an uncertain situation;

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

what probability distributions are and how they are used to aid decision making;
how historical data can be used to find patterns and trends; and report on past performance;
what is statistical reasoning and how it can be applied to aid decision making;
what is hypothesis testing and how hypothesis testing can be used within the statistical modelling process.

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

understand the risks involved in a decision which involves uncertainty, and quantify such risks;
calculate probabilities from theoretical and empirical distributions and use the results to make inferences about decision problem situations;
evaluate the existence of relationships among variables.
identify standard problems involving uncertainty and analyse them with the correct statistical techniques;

Learning and Teaching

Teaching and learning methods

Teaching involves student participation, games, and creative thinking. Students are expected to actively participate in the class. For instance, utilising generally accepted games of chance (such as coin tossing), students engage actively with statistical concepts. Furthermore, case studies are provided during the lectures which ask student to identify and analyse data sets in order to support the development of their problem solving skills and their ability to identify the most appropriate quantitative methods for addressing a given (often uncertain) situation. A full description of each lecture is distributed in advance. In addition to the case studies and activities numerous examples are provided in the lectures. All of these activities contribute to students’ understanding of the subject matter and shape their ability to apply these skills in their assessments. Teaching methods include: Lecturing and multimedia demonstration (video) Learning activities include: Case study, group discussion, game playing-tossing coin, problem solving exercises

Study time
Type	Hours
Teaching	24
Independent Study	126
Total study time	150

Resources & Reading list

Textbooks

Wisniewski, M (2006). Quantitative Methods for Decision Makers. Harlow: Pearson Education.

Morris C (2003). Quantitative Approaches in Business Studies. Harlow: Pearson Education.

Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E (2009). Statistics for Business and Economics. London: Nelson Education Ltd.

Robertson, C (2002). Business Statistics: A Multimedia Guide to Concepts and Applications. London: Arnold Publishers.

Lind, D.A., Marchal, W.G. and Wathen, S. (2007). Statistical Techniques in Business and Economics with Student CD. London: McGraw-Hill Higher Education.

Assessment

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Peer Group Feedback

Assessment Type: Formative
Feedback: Oral feedback will be given for the presentation of the case study and during group discussion.
Final Assessment: No
Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Group Assignment	30%
Written exam	70%

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Breakdown
Method	Percentage contribution
Written exam	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Written exam	100%

Repeat Information

Repeat type: Internal & External