Course code LauZ5164

Credit points 4

Research Methodology in Animal Husbandry

Total Hours in Course160

Number of hours for lectures32

Number of hours for seminars and practical classes32

Independent study hours96

Date of course confirmation26.02.2019

Responsible UnitInstitute of Animal Science

Course developer

author Vadības sistēmu katedra

Līga Paura

Dr. agr.

Course abstract

Students acquire experimental design and experimental data processing methods, as well statistical methods assumptions. During the studies the real examples related to agriculture and livestock are using. Statistical software is provides for problem tasks solving. Students will use data analysis methods 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; apply appropriate experimental design and statistical analysis techniques in students research projects (the practical works are developed, assessment tests are successfully written, successfully passed the theory exam);
skills to define test hypothesis; to choose according to the research project test hypothesis and data analysis method; to interpret results; to formulate conclusions (the practical works are developed, assessment tests are successfully written, home works are developed);
competences in collaboration with supervisor to realize research in bachelor work; to use data analysis methods in research projects and bachelor work (assessment tests are successfully written, home works are developed and defended).

Course Content(Calendar)

1. Introduction to experimental design. The principles of good experiment. [L – 2h]
2. Working with the data set. Database creation and primary processing. [P – 2h]
3. Applied statistics. Presentation of statistical parameters in study works. [L – 2h, P – 2h]
4. Hypothesis testing. Null and alternative hypothesis. Research and statistical hypothesis. [L – 2h]
5. Two paired samples – t-test. [L – 2h, P – 2h]
6. Two independent samples – F-test and t-test. [L – 2h, P – 2h]
7. Calculating how many animals in-group. [L – 2h, P – 2h]
1st test: t-test for experimental data analysis, number of animal in-group. [P – 2h]
8. Experimental design. [L – 2h]
9. Analysis of variance, as experimental data analysis methods. [L – 2h, P – 2h]
10. One-way ANOVA. [L – 2h, P – 2h]
11. Two way ANOVA without replication. [L – 2h, P – 2h]
12. Two way ANOVA with replication. Interaction effect. [L – 2h, P – 2h]
13. Two way ANOVA with replication. Homogeneous and heterogeneous samples. Least square means. [L – 2h, P – 2h]
14. Presentation of ANOVA results in study works. [L – 2h, P – 2h]
15. Correlation and regression analysis. [L – 2h, P – 2h]
16. Use of covariance analysis. [L – 4h, P – 4h]
2nd test: ANOVA, correlation and regression analysis. [P – 2h]

Requirements for awarding credit points

Examination. Examination include a practical tasks on the course subjects and a theoretical subjects acquired during the study course and.
All practical works and two tests should be executed. Two home works 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. Home works has been developed and public defended. Home work: to formulate the aim and three tasks, test the hypotheses using at least 3 statistical methods, based on the data of the master thesis.

Criteria for Evaluating Learning Outcomes

Exam evaluation depends of the semester cumulative assessment: 1st test – 40%, 2nd test – 40% and home work – 20%. 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. Morris, T. R. Experimental design and analysis in animal science. Oxon: CABI Publishing, 1999. 208 p.
2. Mead R., Curnow R.N., Hasted A.M. Statistical methods in agriculture and experimental biology. 2nd ed. London etc.: Chapman and Hall, 1996. 415 p.

Further reading

1. Handbook of data analysis. Edited by M. Hardy, A. Bryman. London ... [etc.]: Sage, 2004. 704 p. 2. Beauchamp T.L., Frey R.G. The Oxford handbook of animal ethics. Oxford, New York: Oxford University Press, 2011. 982 p.

Periodicals and other sources

1. Animal Frontiers: the review magazine of animal Agriculture. American Society of Animal Science.
2. Līdzsvarota lauksaimniecība: zinātniski praktiskās konferences raksti. Latvijas Lauksaimniecības universitāte. Lauksaimniecības fakultāte. Latvijas Agronomu biedrība. Latvijas Lauksaimniecības un meža zinātņu akadēmija. ISSN 2501-0166


Obligatory course for Master study programme “Agriculture” specialisation Livestock