FUNDAMENTALS OF BUSINESS ANALYTICS - 2021/2
Module code: MAN2188
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
This module provides an overall introduction to Business Analytics explaining methods used for descriptive, predictive, and prescriptive analytics as the main building blocks and phases of a typical business project within management and business contexts. In addition to generic introduction to business analytics phases, there will be more focus on the first two phases (i.e.descriptive and predictive small data analytics). This is mainly related to theories of probability and statistics. The module will also include general business skills needed to run a business analytics project such as how analytics professionals communicate with decision makers by using and interpreting analytic models.
Surrey Business School
FU Colin (SBS)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 5
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 117
Lecture Hours: 22
Laboratory Hours: 11
Prerequisites / Co-requisites
The module will cover topics such as:
1. Introduction to the module
2. The Business Analytics lifecycle
3. Descriptive Statistics
5. Probability Theory
6. Descriptive Data Mining
7. Inferential Statistics
8. Regression Theories
9. Time Series Analysis and Forecasting
10. Spreadsheet Models
11. Review of the Module
|Assessment type||Unit of assessment||Weighting|
The assessment strategy is designed to provide students with the opportunity to demonstrate:
• Understanding of the basic concepts of Business Analytics.
• Interpretation and synthesis data for decision making.
• Ability to present data to decision makers in an understandable way.
Thus, the summative assessment for this module consists of:
· Analytics Coursework (40%)
2000 words individual project submitted mid-term.
· Final Examination (60%)
2-hour closed book examination taken at the end of the semester.
· Online assessments tied to lab Students will be given the opportunity to receive formative assessment and feedback relevant to the assignments.
Formative assessment will also be relevant to the closed book exam may be provided on SurreyLearn discussion forums.
· Dedicated feedback on lab session results – common challenges and examples of good practice.
· Individual feedback after online assessment covering key concepts.
- · Introduce students to key theories and concepts relevant to the field of Business Analytics and how it is applied for decision making.
- · To establish knowledge about the main stages of a typical business analytics project how to successfully manage analytics projects.
- · To establish understanding of the different approaches and methods used for business analytics in terms of processes and types of output produced.
|001||Understand the basic concepts of Business Analytics and their importance within the organisation.||CKT|
|002||Critically evaluate and reflect on statistical and probabilistic data analytics methods for businesses.||CP|
|003||Evaluate and interpret data soundly; synthesise data to enhance decisions and conclusions.||CKP|
|004||Ability to present data to decision makers in an understandable way.||KPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
encourage critical understanding of the role played by data analytics for business decision making. Learning will be directed, supported and reinforced through a combination of lectures, computer laps, and online discussion groups, plus directed and self-directed study. The course is research-led and offers a mix of theoretical insights and case study material that will be delivered both online and offline where appropriate.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: MAN2188
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2021/2 academic year.