# Marko Tkalčič

## Teaching

### Programming Project (Spring 2018)

- Course
- Programming Project
- University
- Free University of Bozen-Bolzano, Italy
- Course web page
- http://www.inf.unibz.it/~tkalcic/teaching_pp2017-2018.html

### Decision Support Systems (Fall 2017)

- Course:
- 602.315 (17W) Decision Support Systems
- University
- Alpen-Adria-Universität Klagenfurt, Austria
- Course web page
- https://campus.aau.at/studium/course/91810?lang=en

**Lecture Notes and Other Material**

- 1
- Introduction
- 2
- Modeling Decisions 1
- 2a
- tree-pennzoil-texaco.xlsx
- 3
- Modeling Decisions 2
- 3a
- tornado.xls
- 4
- Modeling Uncertainty 1
- 5
- Modeling Uncertainty 2
- 5a
- goals.xls
- 5b
- MonteCarlo.xls
- 5c
- R code
- 6
- Modeling Preferences
- 7
- Psychological Aspects
- 8
- Clustering
- 8a
- iris.arff
- 8b
- mall.csv

**Instructions for Project**

Project instructions:

- each student has to submit an individual project (no group projects)
- identify a reasonable decision problem with
- 5+ unknown variables
- 2+ objectives

- model the distributions
- at least one variable with historical data (find on-line historical data for the unknown variables)

- apply decision analysis tools as needed
- build the influence diagram
- build the decision tree
- calculate the EMV of all choice paths
- build the risk profile
- perform one-way sensitivity analysis
- build a utility function
- calculate the EV

- apply simulation
- perform a Monte Carlo simulation

- write a report with the following structure
- introduction
- decision problem description
- modeling of unknown variables (include links to online sources)
- decision analysis
- simulation
- conclusion

Submission Instructions

- send report (PDF file) via email to marko.tkalcic@aau.at
- file naming convention: "DSS-Project-studentID.pdf" (e.g. DSS-Project-123456789.pdf)
- email subject line: "DSS-Project-studentID" (e.g. DSS-Project-123456789)
- deadline: 4. December 2017, 23:59 CET

**Project Results**

The results of the project can be found here: results

**Grading**

- There will be a written exam
- Exam-like quick quizzes throughout the course
- Optional: Project (50% of the total exam score)
- Grading:
- score = project assessment score [0-50] + exam score [0-100]
- if score>100 then score=100
- pass score (1,2,3,4) >= 50

**Exam Results**

Results of the exam from 22.12.2017 are available here