Courses list

Wersja polska

Course code: BHN10380o16
Semester: 2016/2017 summer
Name: Basics of Statistics
Major: Animal Science
Study Type: first cycle
Course type: compulsory
Study Semester: 2
ECTS points: 5
Hours (Lectures / Tutorials / Other): 9 / 18 / 0
Lecturer: dr Zofia Kulisiewicz
Language of instruction: Polish


Learning outcomes: Knowledge: Student - 1) knows and understands the concepts of descriptive statistics and basic statistical data analysis 2) understands mathematical description of quantitative traits of animals and plants Skills: Student - 1) describes and analyzes quantitative traits using basic methods of statistics 2) uses information technology to describe and analyze data 3) can presentthe data and results of statistical analysis

Competences: Student: 1) understands the need to improve knowledge of statistics 2) understands the role of statistical methods in breeding work 3) recognizes the importance of access to information and the skills of its processing

Prerequisites: mathematics, proficiency to use Excel

Course content: Basics of probability. Biological traits of population as a random variables. Distribution of a random variable. Population statistical description based on samples. Statistical analysis of the data set. Topics of estimation. Verification of hypotheses (significance tests, compatibility tests). Correlation and simple regression. Univariate analysis of variance.

Recommended literature: Dobek A., Szwaczkowski T.: Statystyka matematyczna dla biologów. Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu, 2007 Łomnicki A.: Wprowadzenie do statystyki dla przyrodników. Wydawnictwo Naukowe PWN, 2012

Assessment methods: Completion of practical training (computer lab) – Part-time course constists of 9 conferences. On meetings 4. and 7. students write 30-minute tests. Students also prepare projects (statistical analysis of the data set). Final grade is an arithmetic mean of both tests and project assessments; to complete the mean not lower than 2,66 is required. Students with the average 4.66 or more do not have to take exam, scoring "very good" for the course. Assessment methods: after completion of practical training (computer lab) students take written exam: 90 minutes, 5 question pointed from 0 to 5, at leat 12 points to pass. Otherwise student can take one more exam (spoken or written).

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