Statistical methods for data analysis

Subject description

Modern graphics for data presentation.

Analysis of contingency tables.

One sample mean and proportion analysis with parametric and nonparametric tests.

Two sample means and proportions analysis with parametric and nonparametric tests.

Analysis of variance; complete random one-way design, randomized complete block design, multi-factor experiment with parametric and nonparametric tests.

The subject is taught in programs

Objectives and competences

Main objective is to give students an overview of concepts and statistical methods for design and analysis of experiments in biological and biotechnical sciences.

Teaching and learning methods

Lectures in computer room; modern software is used. Home work.

Expected study results

Knowledge and understanding: students upgrade basic knowledge of statistics with modern statistical and computing approaches. The focus is on the choice of appropriate methods, on the interpretation of the results and of the use of modern tools for statistical computing.

Basic sources and literature

KOŠMELJ, Katarina. Uporabna statistika. 2. dopolnjena izd. Ljubljana: Biotehniška fakulteta, 2007. ISBN 978-961-6275-26-2. [COBISS.SI-ID 235777024]


Košmelj K.: Interna gradiva.(pdf datoteke)


Mead R, Curnow R & Hasted A. (2002). Statistical Methods in Agriculture and Experimental Biology, Third Edition. Chapman & Hall/CRC Press.


R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL

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