NES3106 : Data & Marketing Analytics
NES3106 : Data & Marketing Analytics
- Offered for Year: 2024/25
- Module Leader(s): Dr Luca Panzone
- Owning School: Natural and Environmental Sciences
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
Pre Requisite Comment
Stage 2 statistics module
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
N/A
Aims
This module builds upon introductory economics and statistics modules to provide students with statistical tools that can be used in economics and marketing analysis. The aim of the module is to offer students the opportunity to:
1) gain an understanding on what statistical techniques can be used to understand and solve marketing problems
and
2) learn how to use state of the art key statistical techniques in data and marketing analysis.
Outline Of Syllabus
The module covers a wide range of analytical methods used in marketing research (e.g. regression analysis, structural equation models, choice modelling, consumer segmentation)
Learning Outcomes
Intended Knowledge Outcomes
On completion of the module students will be able to:
• Understand the role of marketing metrics and the significance of different measurement techniques across a
range of market contexts
• Apply marketing analytics to datasets
• Understand appropriate sources of data for marketing analysis
• Critically assess the value of various analytics tools and techniques for marketing insight and strategic
decision-making
Intended Skill Outcomes
On completion of the module students will be able to:
1. Select and apply appropriate techniques for different marketing research questions
2. carry out data analysis and interpret the results
3. Present the results of data analyses, including conventions for presenting statistical results in written
work
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 40:00 | 40:00 | Preparation for assessment |
| Scheduled Learning And Teaching Activities | Lecture | 8 | 2:00 | 16:00 | Present in Person lecture |
| Guided Independent Study | Independent study | 1 | 44:00 | 44:00 | Revise lecture notes and lecture videos, including reading and watching of supplementary material |
| Total | 100:00 |
Teaching Rationale And Relationship
Core and supplementary material for this module (e.g. lecture slides, datasets, R files and videos) offer students the required resources to:
1) gain an understanding on what statistical techniques can be used to understand and solve marketing problems
2) learn how to use state of the art key statistical techniques in data and marketing analysis.
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 1 | M | 100 | Report |
Assessment Rationale And Relationship
Module assessment consists of one single assignment. A written report will assess your understanding of the statistical techniques covered in the module, both in their use and interpretation of the results.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- NES3106's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- NES3106's past Exam Papers
General Notes
N/A
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Disclaimer
The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.