School of Environmental Sciences

Methods of Biostatistical Analysis

This course is part of the programme:
Master’s study programme Environment (2nd level)

Objectives and competences

The basic objective of Methods of biostatistical analysis is to provide knowledge about the statistical methods needed to identify parameters of individual elements of natural systems (biological and ecological systems), their mutual relations and relationships with environmental factors, which is the basic of the research work for most areas of the environmental science. The course deals with the basic statistical and methodological steps for detection of common factors affecting elements of natural systems and provides a method for the detection of various forms of connections between individual factors as well as methods to test hypotheses. In this course the student acquires basic knowledge to perform biostatistical analyses and develops the ability to critically interpret biostatistical results.

Prerequisites

Biostatistycal analysis relates to subjects of Statistics, Mathematics and biological and ecological subjects from the first year of study.

Content (Syllabus outline)

  • Mass phenomena
  • Elemental parameters
  • Relative numbers
  • Quantile Plots
  • Mean values
  • Measures of Variability, Asymmetry and Kurtosis
  • Theoretical distribution
  • Sampling, estimation of parameters
  • Sampling, small samples
  • Hypotheses and Test procedures
  • Association and Contingency
  • Correlation and Regression
  • Analysis of Covariance
  • Dynamics of the phenomena
  • Classification
  • ordination
  • Statistical design of experiments

Intended learning outcomes

Knowledge and understanding:

By the end of this course student will:

  • be familiar with statistical methods to explore natural systems,
  • be able to interpret the results of simple biostatistical analyzes,
  • know methods to test hypotheses,
  • gain knowledge of the basic methods to design experiments for studying the effects of environment on systems.

Readings

  • Zar, J. H. 1999. Biostatistical Analysis. Fourth Edition. New Jersey, Prentice Hall: 663 str.
  • Ludwig, J. A., Reynolds, J. F. 1988. Statistical Ecology. New York, Chichester, Brisbane, Toronto, Singapore, John Wiley & Sons: 337 str.

Assessment

Written exam (100 %)

Lecturer's references

Assistant Professor of Biochemistry at the University of Nova Gorica

1. LINDIČ, Nataša, BUDIČ, Maruška, PETAN, Toni, KNISBACHER, Binyamin A., LEVANON, Erez Y., LOVŠIN, Nika. Differential inhibition of LINE1 and LINE2 retrotransposition by vertebrate AID/APOBEC proteins. Retrovirology, ISSN 1742-4690. Online ed., 2013, vol. 10, art. no. 156, str. 1-16. http://www.retrovirology.com/content/pdf/1742-4690-10-156.pdf. [COBISS.SI-ID 27367975]

2. LOVŠIN, Nika, PETERLIN, Matija Boris. APOBEC3 proteins inhibit LINE-1 retrotransposition in the absence of ORF1p binding. V: Natural genetic engineering and natural genome editing : proceedings of the GenConText Research Symposium, 3-6 July 2008, Salzburg, Austria, (Annals of the New York Academy of Sciences, ISSN 0077-8923, vol. 1178, no. 1, 2009). New York: New York Academy of Sciences, 2009, vol. 1178, no. 1, str. 268-275. [COBISS.SI-ID 23252263]

tipologija 1.08 -> 1.01

3. AGUIAR, Renato S., LOVŠIN, Nika, TANURI, Amilcar, PETERLIN, Matija Boris. VPR.A3A chimera inhibits HIV replication. The Journal of biological chemistry, ISSN 0021-9258, 2008, vol. 283, no. 5, str. 2518-2525, ilustr. [COBISS.SI-ID 21302823]

4. OKEOMA, Chioma M., LOVŠIN, Nika, PETERLIN, Matija Boris, MARKI, Susan Ross. APOBEC3 inhibits mouse mammary tumour virus replication in vivo. Nature, ISSN 0028-0836, 2007, vol. 445, no. 7130, str. 927-930. [COBISS.SI-ID 20903975]

5. LOVŠIN, Nika, GUBENŠEK, Franc, KORDIŠ, Dušan. Evolutionary dynamics in a novel L2 clade of non-LTR reprotransposons in Deuterostomia. Molecular biology and evolution, ISSN 0737-4038, 2001, vol. 18, str. 2213-2224. [COBISS.SI-ID 16295719]

University course code: 2OK028

Year of study: 1

Semester: 1.

Course principal:

Lecturer:

ECTS: 6

Workload:

  • Lectures: 30 hours
  • Exercises: 15 hours
  • Individual work: 135 hours

Course type: elective

Languages: slovene and english

Learning and teaching methods:
lectures, tutorial