Experimental design and analysis

This course is part of the programme
Master’s study programme Viticulture and Enology

Objectives and competences

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.


Basic statistical and mathematical knowledge.


  • 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.

Intended learning outcomes

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%)

Lecturer's references

Prof. dr. Irina Cristea

Principal education and research areas: Mathematics, algebraic hyperstructures and connections with fuzzy sets and their generalizations; mathematical models based on cluster analysis (hard and fuzzy version).
Professional career: Prof. dr. Irina Elena Cristea received the PhD in Mathematics, with specialization in Algebra, in 2007, from the University of Constantza, Romania. She started the research career in 2003 at the University of Iasi, Romania, where she worked as Teaching Assistant for 4 years. After a post doctoral position at Udine University, Italy, since January 2012 she is employed at the University of Nova Gorica, as Associate Professor in Mathematics, conducting research in Algebraic Hyperstructure Theory, being affiliated with the Centre for Information Technologies and Applied Mathematics. She is currently teaching Mathematics at the School of Engineering and Management, School of Environmental Sciences, School of Applied Sciences.

Selected bibliography

  • DAVVAZ, Bijan, CRISTEA, Irina Elena. Fuzzy algebraic hyperstructures : an introduction, (Studies in fuzziness and soft computing, vol. 321). Cham: Springer, cop. 2015. X, 242 str., ilustr. ISBN 978-3-319-14761-1 [COBISS.SI-ID 3704571]
  • DAVVAZ, Bijan, HASSANI SADRABADI, E., CRISTEA, Irina Elena. Atanassov's intuitionistic fuzzy grade of complete hypergroups of order less than or equal to 6. Hacettepe journal of mathematics and statistics, ISSN 1303-5010, 2015, vol. 44, no. 2, str. 295-315 [COBISS.SI-ID 3888123]
  • CRISTEA, Irina Elena, DAVVAZ, Bijan, HASSANI SADRABADI, E. Special intuitionistic fuzzy subhypergroups of complete hypergroups. Journal of intelligent & fuzzy systems, ISSN 1064-1246. 2015, vol. 28, no. 1, str. 237-245. [COBISS.SI-ID 3454203]
  • JAFARPOUR, Morteza, CRISTEA, Irina Elena, ALIZADEH, F. On dihedral hypergroups. European journal of combinatorics, ISSN 0195-6698, 2014, vol. 44, part B, str. 242-249,[COBISS.SI-ID 3520251]
  • CRISTEA, Irina, ŞTEFANESCU, Mirela, ANGHELUŢA, Carmen. About the fundamental relations defined on the hypergroupoids associated with binary relations. Eur. j. comb., 2011, vol. 32, no. 1, str. 72-81. [COBISS.SI-ID 2062587]
  • CRISTEA, Irina, DAVVAZ, Bijan. Atanassov's intuitionistic fuzzy grade of hypergroups. Inf. sci. [Print ed.], 2010, vol. 180, no. 8, str. 1506-1517. [COBISS.SI-ID 2065915]