Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
Students learn
- to analyze and develope business models for digital and service business
- quantitative modeling using simulation techniques which can be used to support management decision making in digital and service businesses, in finance, in operations management, and in logistics etc.;
- to develop their expertise in using simulation models with computers and related software, especially Excel;
- to analyze results and making decisions through assigned homework exercises and case analyses; and
- to design research.
Credits: 6
Schedule: 07.09.2020 - 22.10.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Tomi Seppälä
Teacher in charge (applies in this implementation): Tomi Seppälä
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
Introduction to simulation models, simulation with computers, random numbers, probability distributions, methods to simulate random events, managerial applications of risk analysis, probability theory, stochastic processes Random walk models, multivariate distributions, inventory simulation, service system simulation, forecasting
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
75% exam
25% assignments
Workload
Valid 01.08.2020-31.07.2022:
Contact teaching 36 h
Independent work 121 h
Exam 3 h
Total 160 h
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
1. Evans, J.R. & Olson, D.L. (2002) Introduction to simulation and risk analysis (selected parts)
2. Ross, Sheldon M. (2006) Simulation (selected parts).;
3. Vose, D. (2000) Risk analysis: a quantitative guide (additional readings)
Prerequisites
Valid 01.08.2020-31.07.2022:
Undergraduate mathematics, statistics and probability, as well as Excel skills. More specifically, basic knowledge in probability calculations and distributions, statistical analysis, matrix algebra, differential and integral calculus and are essential. At the minimum two courses in university statistics and one course in university mathematics is assumed.
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