Module overview
The module will cover some of the most important marketing analytic techniques that you will face as a data analyst, exploring ways to create dynamic synthetic visuals that communicate your analysis to various audiences.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Critically analyse, interpret, organise and visualize quantitative data in synthetic visuals.
- Integrate, prepare, and manage quantitative data.
- Identify suitable approaches for incorporating insights into marketing tasks.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Communicate ideas and arguments in various formats.
- Use specified software packages to conduct the marketing analytics techniques.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- How various analytical and visualization techniques can be used to uncover the potential of data to gain actionable insights and support marketing decisions.
Syllabus
The topics covered include:
- Core descriptive statistics, standard distributions, hypothesis testing
- Evaluation of data and usage;
- Presentation of data: Graphics, tables, synthetic visuals
- The use of analytical software packages to conduct marketing analysis and visualizations.
Learning and Teaching
Teaching and learning methods
The focus of this module will be to actively engage you in the subject matter through guided self-discovery of the material. Lectures will be used to set the agenda and further develop the material specified in the reading list and in other sources recommended throughout the semester.
Type | Hours |
---|---|
Independent Study | 126 |
Teaching | 24 |
Total study time | 150 |
Resources & Reading list
Textbooks
Knapp, Herschel (2017). Introductory Statistics using SPSS. Sage.
Cortinhas, C. and Black, K. (2012). Statistics for Business and Economics. Wiley.
Winston, W. L (2014). Marketing Analytics: Data-Driven Techniques with Microsoft Excel. Somerset: J Wiley and Sons.
Jelen, Bill, and Alexander, M. (2016). Excel 2016 Pivot Table Data Crunching. Pearson Education.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Feedback
- Assessment Type: Formative
- Feedback: During tutorial sessions, students will discuss on assigned exercises and receive answers on their questions
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Report | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Report | 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.
Method | Percentage contribution |
---|---|
Report | 100% |
Repeat Information
Repeat type: Internal & External