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Objectives and competences

• understanding of some advanced concepts in statistics • ability to apply such knowledge and understanding to the solution of practical problems • computational and data-processing skills • competence in the planning experiments, collecting, analyzing and interpreting data • ability to evaluate critically the empirical research

Content (Syllabus outline)

• design and analysis of experiments • linear regression • multiple linear regression • analysis of one-factor experimental designs • analysis of multi-factor experimental designs • multiple comparisons tests • analysis of covariance • ANOVA for repeated measures • Wilcoxon signed-ranks test • Mann-Whitney U test • Kruskal-Wallis one-way analysis of variance • Friedman two-way analysis of variance • concordance analysis • correlation and partial correlation • McNemar test • analysis data with statistical software and interpretation the results

Learning and teaching methods

lectures tutorials computer practical self-study

Intended learning outcomes - knowledge and understanding

Knowledge and understanding: Students should be able: • to comprehend the basic ideas of statistical inference, study design and data collection relevant to experiments that are typical for the natural sciences. • to determine the appropriate parametric or nonparametric statistical test, given the research question and the type of data. • to carry out the needed analyses for the discussed situations and interpret the results in terms of the problem. • to carry out the analyses, with the help of SPSS (for not so complex procedures also without statistical program), interpret the results, and formulate conclusions in terms of the actual problem. • to recognize pitfalls in using statistical methodology. • to know statistical terminology in English.

Intended learning outcomes - transferable/key skills and other attributes

Readings

• Košmelj, K. 2004. Osnove analize kovariance, Acta agriculturae slovenica, 83 – 2. Dostopno na: http://aas.bf.uni-lj.si/november2004/13kosmelj.pdf • Vasilj, Đ. 2000. Biometrika, Hrvatsko agronomsko društvo, Zagreb. • Sheskin, D.J. 2000. Handbook of parametric and nonparametric statistical procedures, Chapman&Hall/CRC. • Hadživuković, S. 1991. Statistički metodi, Poljoprivredni fakultet, Novi Sad.

Prerequisits

None.

  • doc. dr. TADEJA KRANER ŠUMENJAK

  • Written examination: 50
  • Practical exam: 50

  • : 25
  • : 15
  • : 60

  • Slovenian
  • Slovenian

  • AGRICULTURE - 1st