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Research Methodology and Biostatistic

Course developers

Prior knowledge

Biol3014, Plant Physiology I

Vete2022, Animal Physiology

Course abstract

Students acquire experimental design and experimental data processing methods, as well presentation of the results in study works. During the studies the real examples related to agriculture are using. Statistical software is provides for problem tasks solving. Students will use theoretical and practical knowledge in research projects and bachelor work.

Learning outcomes and their assessment

After completing the course student will have: knowledge and critical understanding about experimental design and data analysis methods; acquire knowledge on principles of Bachelor thesis’ structure (the practical works are developed, assessment tests are successfully written, successfully passed the theory exam);
skills to choose according to the experimental design hypothesis and data analysis method; to interpret and evaluate results; to formulate conclusions (the practical works are developed, assessment tests are successfully written, home work are developed);
competences in collaboration with supervisor to realize research for bachelor work; to use data analysis methods, evaluate and complete the results to tables and graphs in research projects and bachelor work (assessment tests are successfully written, home works are developed and defended).

Course Content(Calendar)

1. Introduction to research design. [L- 2h]
2. The scientific methods. [L- 2h/ P – 2h]
3. Experiment model design for field and livestock research. [L- 2h/ P – 2h]
4. Planning of experimental study. Tools of research. [L- 2h/ P – 2h]
1st test: Research design and methodology. [P – 2h]
5. Descriptive statistics. Presentation of descriptive statistical parameters in study works. [L- 2h/ P – 2h]
6. Correlation analysis. [L- 2h/ P – 2h]
7. Regression analysis. [L- 2h/ P – 2h]
8. Hypothesis testing. Null and alternative hypothesis. Research and statistical hypothesis. [L- 2h]
9. Two paired samples – t-test. [L- 2h/ P – 2h]
10. Two independent samples – F-test and t-test. [L- 2h/ P – 2h]
11. One-way ANOVA. [L- 2h/ P – 2h]
12. Two way ANOVA without and with replication. [L- 2h/ P – 2h]
2nd test: Descriptive statistics, ANOVA, correlation and regression analysis. [P – 2h]
13. Structure of study projects. [L- 1h/ P – 3h]
14. Literature review and list of bibliography sources. [L- 3h/ P – 1h]
15. Study results formatting and presentation in tables and graphs. [L- 1h/ P – 3h]
16. Study results and discussion, conclusions. [L- 3h/ P – 1h]
Homework presentation.

Requirements for awarding credit points

Examination. Examination include a practical tasks on the course subjects and a theoretical subjects acquired during the study course.
All practical works and two tests should be executed before examination. Homework has been developed and public defended.

Description of the organization and tasks of students’ independent work

The organization of independent work during the semester is independently studying literature, using academic staff member consultations. Homework has been developed and public defended. Homework - 2-3 pages: to formulate the aim and two tasks, test the hypotheses using at least 2 statistical methods, based on the experimental data. Complete tables or graphs from the results, write conclusions.

Criteria for Evaluating Learning Outcomes

Exam evaluation depends of the semester cumulative assessment: 1st test – 20%, 2nd test – 20%, homework – 20%, and written examination during the session – 40%. Students who have a cumulative assessment of the study course less than 4 or wish to improve it (at least 4) hold the complex exam during the session. The exam includes practical part (60%) and theory (40%).

Compulsory reading

1. Marczyk G., DeMatteo D., Festinger D. Essentials of Research Design and Methodology. Hoboken, New Jersey: , John Wiley & Sons, Inc., 2005. 305 p.
2. Mead R., Curnow R.N. and Hasted A.M. Statistical methods in agriculture and experimental biology. 2nd ed. London etc.: Chapman and Hall, 1996. 415 p.
3. Gustavii B. How to write and illustrate scientific papaers. Cambridge: Cambridge University Press, 2008. 168 p.

Further reading

1. Handbook of data analysis. Edited by M. Hardy, A. Bryman. London ... [etc.]: Sage, 2004. 704 p.
2. Beauchamp T. L. and Frey R.G. The Oxford handbook of animal ethics. Oxford, New York: Oxford University Press, 2011. 982 p.
3. Petersen R. G. Agricultural Field Experiments Designe and Analysis. Oregone State Universit, 1994. 409 p. https://www.taylorfrancis.com/books/9780429078491

Periodicals and other sources

1. Animal Frontiers: the review magazine of animal Agriculture. American Society of Animal Science. ISSN: 2160-6064

Notes

Obligatory course for BSc study programme “Sustainable Agriculture”