Experimental design and analysis

Proper experimental design is a prerequisite to the efficient and cost effective resolution of comparative quantitative research questions. This subject introduces experimental design and analysis through the use of examples and by the study of underlying linear model. Use of appropriate computer packages allows testing of assumptions and investigation of advanced topics. Extensions of the basic methodology are explored. Students will gain experience in evaluating and presenting results in the form of a standard statistical report as used in professional practice. The experiences will be used in the evaluation of the results of different experiments (scientific and professional) in the field.

Admission to the first and second year of study program.

• Principles of experimental design.
• Simple linear regression: review and extension.
• Polynomial and multiple linear regression.
• Principles of experimental design; including completely randomized designs, randomized block designs and Latin square designs.
• Multiple comparison methods.
• Diagnostic checking of the basic model.
• The analysis of experiments with factorial treatment structures.
• Analysis of variance.
• Analysis of covariance.
• Statistical software.

Knowledge and understanding:
• be able to identify situations for which a linear model is appropriate;
* be able to design, and check the design of standard experiments reflective of professional practice;
* be able to perform the analysis of such experiments using appropriate statistical protocols;
* be able to communicate results and justify interpretations in terms of the original problem with logic and precision;
* be able to evaluate and present results, with an integrated understanding of the underlying theory, in the form of a standard statistical report;
* be able to critically test any assumptions underpinning the use of the linear model;
* be able to perform design and analysis tasks on recognized software platforms

1. Gary W. Oehlert, A first Course in Design and Analysis of Experiments, 2010, E-version
2. Howard J. Seltman, Experimental Design and Analysis,2015, E-version
3. Adamič Š. (2005).Temelji biostatistike, Medicinska fakulteta Ljubljana, 1995.
4. Košmelj, K. (2007). Uporabna statistika. Ljubljana: Univerza v Ljubljani, Biotehniška fakulteta E-version
5. A. Vadnjal, Elementarni uvod v verjetnostni račun, DZS, Ljubljana, 1979. Catalogue
6. Internet resources for learning statistics
7. Moodle classroom
8. Slides from lectures

Seminar work and homeworks (30%), written exam (70%)

Professional career:
Asst. Prof. Adrian Hermes did his PhD at Saarland University (Germany) and Sabanci University (Turkey) in Industrial Engineering-Operations Research (with a minor in Computer Science). After his doctoral studies, he participated in two national projects in Industrial Optimization, Logistics, Systems Engineering, and Forest Engineering (as a postdoctoral research associate) in different departments of Umeå University (Sweden), where he was also a lecturer/supervisor in the Industrial Engineering, Management, and Mathematics.
He is primarily interested in interdisciplinary research at the intersection of Industrial Engineering, Operational Research (OR), Computer Science, Applied Mathematics, and Data Analytics, with a focus on theory, design, and implementation. In particular, he is interested in modeling and solving combinatorial & industrial optimization problems in Supply Chains, System Engineering, Manufacturing, Logistics & Distribution, Forest Engineering/Planning, and Transportation. His research is mainly based on mathematical programming techniques, network optimization algorithms, heuristics, and a combination of heuristics/metaheuristics with exact/approximation/stochastic optimization techniques.
He is currently an Assistant Professor at the School of Engineering and Management (PTF) and the School of Viticulture and Enology at the University of Nova Gorica, being affiliated with the Centre for Information Technologies and Applied Mathematics.

Selected publication:

• ČESNIK, Urban, MARTELANC, Mitja, OVSTHUS, Ingunn, RADOVANOVIĆ, Tatjana, HOSSEINI, Ahmad, MOZETIČ VODOPIVEC, Branka, BUTINAR, Lorena.
  Functional characterization of Saccharomyces yeasts from cider produced in Hardanger.
  Fermentation. 2023, vol. 9, issue 9, [article no.] 824, str. 1-27. ISSN 2311-5637.
  DOI: 10.3390/fermentation9090824. [COBISS.SI-ID 164729091], [JCR, SNIP, Scopus]
• HOSSEINI, Ahmad, WADBRO, Eddie, NGOC DO, Dung, LINDROOS, Ola
  A scenario-based metaheuristic and optimization framework for cost-effective machine-trail network design in forestry. Computers and electronics in agriculture. [Print ed.]. Sep. 2023, vol. 212, [article no.] 108059, str. 1-13, ilustr. ISSN 0168-1699. DOI: 10.1016/j.compag.2023.108059. [COBISS.SI-ID 159537155], [JCR, SNIP, WoS, Scopus]
• HOSSEINI, Ahmad, WADBRO, Eddie.
  A hybrid greedy randomized heuristic for designing uncertain transport network layout. Expert systems with applications. [Print ed.]. Mar. 2022, vol. 190, [article no.] 116151, str. 1-10, ilustr. ISSN 0957-4174.
  DOI: 10.1016/j.eswa.2021.116151. [COBISS.SI-ID 141605891], [JCR, SNIP, WoS, Scopus]
• HOSSEINI, Ahmad, PISHVAEE, Mir Saman.
  Capacity reliability under uncertainty in transportation networks: an optimization framework and stability assessment methodology. Fuzzy optimization and decision making. Sep. 2022, vol. 21, iss. 3, str. 479–512, ilustr. ISSN 1568-4539. DOI: 10.1007/s10700-021-09374-9. [COBISS.SI-ID 141610755], [JCR, SNIP, WoS, Scopus]
• NAKHAEI, Niknaz, EBRAHIMI, Morteza, HOSSEINI, Ahmad.
  A solution technique to cascading link failure prediction. Knowledge-based systems. [Print ed.]. Dec. 2022, vol. 258, [article no.] 109920, str. 1-14, ilustr. ISSN 0950-7051.
  DOI: 10.1016/j.knosys.2022.109920. [COBISS.SI-ID 141591555], [JCR, SNIP, WoS, Scopus]
• HOSSEINI, Ahmad, PISHVAEE, Mir Saman.
  Extended computational formulations for tolerance-based sensitivity analysis of uncertain transportation networks.
  Expert systems with applications. [Print ed.]. Nov. 2021, vol. 183, [article no.] 115252, str. 1-19, ilustr. ISSN 0957-4174. DOI: 10.1016/j.eswa.2021.115252. [COBISS.SI-ID 141608451], [JCR, SNIP, WoS, Scopus]
• HOSSEINI, Ahmad, LINDROOS, Ola, WADBRO, Eddie.
  A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines. Canadian journal of forest research. 2019, vol. 49, no. 2, str. 111-120, ilustr. ISSN 0045-5067.
  DOI: 10.1139/cjfr-2018-0258. [COBISS.SI-ID 141605635], [JCR, SNIP, WoS, Scopus