ECTS
ECTS Course Catalogue

Course details
Course code: BHS20077o12
Semester: 2012/2013 summer
Name: MATEMATICAL STATISTICS
Major: Animal Science
Study Type: second cycle
Course type: compulsory
Study Semester: 1
ECTS points: 7
Hours (Lectures / Tutorials / Other): 30 / 30 / 0
Lecturer: dr hab. Joanna Szyda, prof. nadzw.
Language of instruction: Polish / English
possible german

Learning outcomes: During the course students learn basics of mathematical statistics theory, as well as gain skills to use the knowledge in practical data analysis. In particular, students learn how to perform descriptive statistics, hypotheses testing, statistical inference, model correlations between variables and the variability of a trait. The skills allow for carrying statistical data analysis and interpreting results of such analysis.

Competences: Passing the course allows students to carry out a statistical analysis of data for their master thesis, including the choice of appropriate methodology as well as interpretation of own and other authors results. After completion of the course, students possess skill enabling them to work in institutions dealing with statistical data analysis and interpretations, such as breeding centers and biomedical companies.

Prerequisites:

Course content: Probability, distributions, populations and samples, hypotheses testing, parameter estimation, examples of parametric and nonparametric statistical tests, regression, correlation, analysis of variance.

Recommended literature: DeGROOT. M. (1989) Probability and statistics. Addison-Wesley publishing Company DRAPER, N.R., SMITH, H. (1998) Applied Regression Analysis, Wiley HAWKINS D. (2005). Biomeasurement. Understanding, analysing, and communicating data in the biosciences. Oxford University Press MAGIERA R. (2007). Modele i metody statystyki matematycznej. Oficyna Wydawnicza GiS KRZYƚKO M. (1996). Statystyka matematyczna. Wydawnictwo Naukowe Uniwersytetu im. Adama Mickiewicza w Poznaniu

Assessment methods: Completion of laboratory training Exam Minimum 70% of knowledge to pass

Comment: