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Methodology of Research in Agronomy

Course developers

Course abstract

The aim and tasks of the course:
- provide knowledge of the general principles of analysis and modeling of the dynamic systems, particularly in relation to the topic of the chosen doctoral thesis;
- look at the latest research methods' options in the chosen sub-field of science or research direction;
- deepen and expand the skills of professional interpretation of the results of mathematical data analysis, applying them to topics of the doctoral thesis;

- ensure high-quality data mathematical analysis and professional interpretation of results in the dissertation.

Learning outcomes and their assessment

Academic competencies:
- knowledge of dynamic systems modeling principles;
- knowledge of the theory and application of various statistical methods;
- knowledge of the principles of planning, implementation, and approbation of research work.
Professional competencies:
- concepts and principles of dynamic systems modeling and various statistical methods are mastered.
- ability to interpret and apply them in the context of the chosen topic of doctoral thesis, using the programs Vensim, MS Excel, SPSS and R;
- improved independent work skills in the literature analysis, dynamic system modeling, statistics and other research methods.

The control of the level of skills and competence is based on the presentation of the research methods and data analysis and display chosen in the dissertation and the argumentation of the used methods.

Course Content(Calendar)

Main course topics:
- Scientific method, data acquisition and presentation
- Modeling of dynamic systems
- Research design
- Sampling method
- Hypothesis testing - parametric methods
- Hypothesis testing - nonparametric methods
- Correlation and linear regression
- Multifactor analysis
- Time series analysis
- Publication and presentation of scientific research, requirements for doctoral thesis. Organization of scientific work. Financing and management of scientific projects.

Main tasks:
1. In the context of research methodology, to specify the variables of doctoral research, topicality of research, aim and tasks, hypothesis, number of observations necessary for research, and applicable data analysis methodology. During the study process to learn how theoretical knowledge can be applied to specific agricultural science research tasks.
2. Preparation for practical - seminar classes on the possibilities of applying the topics considered in the theoretical lectures in the dissertation research. Preparation for discussions and reports of the results of independent work on the chosen topic. The topic is chosen by the doctoral student, linking it with research interests. During the seminar, the ability to analyze the chosen system using elements of mathematical modeling and professional interpretation of the results of data mathematical processing must be demonstrated.
3. Choose literature and create an annotated bibliography according to the research direction.

4. In accordance with the aim and tasks of the dissertation, to create a professionally substantiated version of the data analysis and conclusion scheme. To prepare for the presentation of the data processing approach and professional analysis of the results respective to the selected dissertation theme.

Requirements for awarding credit points

Form of examination - oral exam, which will be evaluated in a 10-point system.
The ability to raise scientific problems and find solutions during the discussion on research methodology in connection with the dissertation theme will be assessed.

Description of the organization and tasks of students’ independent work

The sequence of independent work with the description of tasks is indicated in the course content description.

Criteria for Evaluating Learning Outcomes

In addition to the knowledge and competence assessment criteria mentioned in the learning outcomes section, the evaluation will include discussing a range of questions related to in-depth study results about the dissertation theme.

Compulsory reading

Iespējamo pamat literatūru doktoranti izvēlās atbilstoši sākotnējo zināšanu līmenim par pētījumu metodiku lauksaimniecībā un arī padziļinātās specializācijas virzienos saistībā ar promocijas darba tēmu.
Iespējamās pamat literatūras saraksts par pētījumu metodiku:
1. Arhipova I., Bāliņa S. Statistika ekonomikā. Risinājumi ar SPSS un Microsoft Excel. Rīga: Datorzinību centrs, 2003.
2. Field., A., Doscovering Statistics Using SPSS. SAGE Publications, 2005.
3. Goša Z. Statistika. Rīga: LLU, 2003.
4. Haefner James W. Modeling biological systems: Principles and applications. –New York etc.: Chapman and Hall: Thomson, 1996.
5. Hardy M., Bryman A., Handbook of data analysis. SAGE Publications, 2004.
6. Krastiņš O. Statistika un ekonometrija. Mācību līdzeklis augstskolām.- Rīga, LR Centrālās statistikas pārvalde, 1998.
7. Teetor, P., ”R Cookbook: Proven recipes for data analysis, statistics, and graphics”, O’Reilly Media, 2011.
8. Peterson R.G. Agricultural Field experiments Desing and Analysis, Oregon State University, 1994.
9. Pruyt, E. Small system dynamics models for big issues: Triple jump towards real-world complexity, 2013.
10. Raykov, T., Marcoulides, G. A. Basic Statistics – An Introduction with R, 2013.
11. Sahu, P.K. Applied Statistics for Agriculture, Veterinary, Fishery, Dairy and allied Fields. Springer, 2016.
12. Wassermann L. All of nonparametric statistics, Springer, 2006.

13. Winston, C. ”R Graphics cookbook: practical recipes for visualizing data”, 2013.

Further reading

Papildliteratūru doktoranti izvēlās atbilstoši savam pētnieciskā darba virzienam. Padziļinātā problēmas izpēte pamatojas uz zinātnisko publikāciju, vispirms SCI (Agricultural Research, Weed Research u.c.) izmantošanu.

Periodicals and other sources

1. LLU Raksti .- Jelgava, LLU //Rakstu krājumu formāts : http://llufb.llu.lv/proceedings/n26/LLU-raksti-nr26.pdf
2. Agronomijas Vēstis. - Jelgava : LLU.//Rakstu krājumu formāts: LLU Fundamentālā bibliotēka, LLU konferenču materiāli .https://lira.lanet.lv/F/?func=find-b-0&local_base=llu07

Notes

Compulsory course for the doctoral study program of the Faculty of Agriculture in the field of Agricultural Sciences in the sub-fields of Field Crops, Horticulture and Zootechnic. Promotion examination.
Prerequisites: Master's program level knowledge in the chosen specialty and biometrics.