Business Analytics, Applied Modelling and Prediction
- Students will study analysis in the business theoretical background
- Students will discuss and analyse business processes based on a case of bakery manufacturing
- The goal of the course is to give students a better grasp of quantitative subjects.
- This course provides students with an ability to handle a range of mathematical and statistical models which helps them be more inquisitive, more precise, more accurate in their statements, more selective in their use of data.
- The course extends and reinforces existing knowledge and introduces new areas of interest and applications of modelling in the ever-widening ﬁeld of management.
- Students will create and discuss financial plan for a start-up
- At the end of the course and having completed the essential reading and activities students should be able to apply modelling at varying levels to aid decision-making.
- Students should be able to understand basic principles of how to analyse complex multivariate datasets with the aim of extracting the important message contained within the large amount of data which is often available.
- Students should be able to demonstrate the wide applicability of mathematical models while, at the same time, identifying their limitations and possible misuse.
- Data. Structured data types. CSV, XML, JSON, YAML. Excel simplest applications. Bakery component description in YAML.
- Course structure. Requirements and deliverables. Semantic model of problem. Ontology of Case 1. Bakery (COS Block 1)
- Introduction to the course, overview, assessment, Monty Hall problem (LSE Block 1)
- ABCD analysis in excel. Histogram in Excel.
- Processes, actions and events. BPMN.
- Tracks arriving schedule analysis and simulation
- Events in the time. Poisson point process.
- Tracks arriving schedule analysis and simulation.
- Descriptive statistics, relationships between variables, Tableau (LSE Blocks 2, 3 and 4)
- Probability, distributions, decision trees (LSE Blocks 5, 6 and 7)
- Business Monthly Unit 1
- Business Monthly Unit 2
- Business Monthly Unit 3
- Business Course Work and ExamThe exam may be carried out online via distance learning platforms.
- Business Course Final Work
- UoL Exam
- UoL Exam
- Interim assessment (2 module)Grade=Business Course Work and Exam*0.4 + (Business Monthly Unit 1+Business Monthly Unit 2+Business Monthly Unit )*0.2
- Interim assessment (4 module)BU2=Business Course Final Work2*0.7 + (Business Monthly Unit4+Business Monthly Unit5+Business Monthly Unit6)*0.1
- Nabavi, M., & Olson, D. L. (2019). Introduction to Business Analytics. New York: Business Expert Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1922612
- Rao, U. H., & Nayak, U. (2017). Business Analytics Using R - A Practical Approach. [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1406793