Quantitative Methods

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);
• collect relevant data and summarise the main features of an uncertain situation;
• work effectively in a team.

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• evaluate the existence of relationships among variables.
• identify standard problems involving uncertainty and analyse them with the correct statistical techniques;
• 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;

Knowledge and Understanding

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

• what is hypothesis testing and how hypothesis testing can be used within the statistical modelling process.
• 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 probability distributions are and how they are used to aid decision making;

• Statistical reasoning, repeated experiments, random variables.
• Measures of central tendency and spread. Statistical moments.
• Symmetry and pointedness.
• Confidence limits.
• Standardised data.
• Extreme observations.
• Continuous and discrete data.
• Introduction to probability.
• Addition and multiplication rules.
• The method of maximum likelihood.
• Probability distribution.
• Cumulative probability distribution.
• Simulation as a tool to solve statistical problems.
• Pseudo-random numbers.
• Some standard distributions: Binomial distribution, Poisson distribution, Normal distribution, Chi-square distribution.
• Sampling of quality.
• The characteristic function of a sampling plan.
• The power of a statistical test.
• Hypothesis testing.
• Analysis of contingency tables.
• Combination of random variables.
• Central limit theorem.
• Association and correlation.
• Measures of association.
• Linearity and non-linearity.
• Spurious correlation.
• Regression.
• Least squares.
• T-tests.
• Serial correlation.

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

Resources & Reading list

Textbooks

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

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.

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

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

Formative

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

Summative

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

Referral

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

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.

Repeat Information

Repeat type: Internal & External