Course code MežZ3077

Credit points 3

Methodology of Research

Total Hours in Course81

Number of hours for lectures24

Number of hours for seminars and practical classes8

Independent study hours49

Date of course confirmation02.03.2021

Responsible UnitInstitute of Forest Management

Course developers

author prof.

Linards Sisenis

Dr. silv.

author lect.

Solveiga Luguza

Mg. silv.

Prior knowledge

Mate1035, Mathematics II

Mate4016, Mathematics I

Course abstract

Aim of the study course is to provide a basic understanding of science, the role of technical progress in the promotion and innovation, to create an understanding of the content and sequence of scientific work, to provide knowledge and skills to the students to be able to independently choose the research topic, to work out previous research survey, choose the research methodology, to describe it and accordingly use it, to obtain the data, to process using suitable mathematical methods, and be able to analyze the results.

Learning outcomes and their assessment

After course of Methodology of Research students know the basic empirical data processing techniques, (test), using logical analysis can select specific data suitable mathematical methods as well as is competent in planning trials or eksperiments (test), taking into account the type and extent of empirical data needed to solve specific research tasks.(test)

Course Content(Calendar)

Course Content(Calendar)
LECTURES
1. Definition of science, division. Law on Scientific Activity. 1h
2. Scientific work, choice of research topic, formulation of goal, tasks and hypothesis. 2h
3. Structure of scientific work, structure of review of previous research and specifics of development. 1h
4. Choice of work methodology, structure and development of methodology description.1h
5. Development of results department, compilation and interpretation of results. 2h
6. Development of conclusions and proposals of scientific work, design of pictures and tables, 3h, 1st test.
7. Design and defense of the work, preparation of the presentation. 2h
8. The structure and tasks of the structure of the university and scientific institute. 1h
Test 2.
9. Cognitive deductive and inductive solution. Statistical sets. 1 h
10. Statistical indicators, their classification. Averages. Dispersion rates. Representativeness indicators. 2 h
11. Evaluation in statistics. Classification of theoretical distributions and empirical distributions. Normal distribution. 1 h
12. Hypothesis testing. Null hypothesis. 1 h
13. Verification of the correspondence between the empirical and normal distributions. Comparison of sample groups. Aggregation of samples. 1 h
Test 3.
14. Conditions and interpretation of variance distribution. Basic tasks of variance analysis. 2 h
Test 4.
15. Dependence of features and infrastructure. Types of correlation. Scatterplot. Correlation strength indicators. 1 h
16. The concept of regression. Basic tasks of regression analysis. Choice of regression type. 2 h
Test 5.
PRACTICAL WORKS
1. Calculation and analysis of statistical indicators of the sample. 1 h
2. Calculation of representation intervals in the general group. 2 h
3. Hypothesis testing. 1 h
4. Analysis of variance. 2 h
5. Correlation analysis. 1 h 6. Regression analysis. 1 h

Requirements for awarding credit points

It is necessary to successfully write 5 tests, which are planned outside the lessons, in coordination with the lecturer. 6 practical works must be completed and defended.

Description of the organization and tasks of students’ independent work

Independently study the available literature.

Criteria for Evaluating Learning Outcomes

It is necessary to successfully write 5 tests, which are planned outside the lessons, in coordination with the lecturer. 6 practical works must be completed and defended. In the end, an accumulative test, evaluation is formed from the marks of tests and practical work evaluation. Execution of overdue practical work and passing the failed tests within the time set by the department.

Compulsory reading

1. Studiju noslēguma darbu struktūra un noformēšana: metodiskie norādījumi Meža fakultātes studentiem [tiešsaiste]. Sast. L.Sisenis, A. Ābele. . Latvijas Lauksaimniecības universitāte Meža fakultāte. Jelgava: LLU, 2015. 18 lpp. [Skatīts 10.02.2017.]. Pieejams: http://www.mf.llu.lv/getfile.php?id=1383
2. LLU Satversme [tiešsaiste] [skatīts 10.02.2017.]. Pieejams: http://www.llu.lv/lv/llu-pamatdokumenti
3. Zinātniskās darbības likums LR likums [tiešsaiste]. Pieņemts 14.04.2005. Stājas spēkā 19.05.2005. . Pieejams: http://likumi.lv/doc.php?id=107337
4. Arhipova I., Bāliņa S. Statistika ekonomikā. Risinājumi ar SPSS un MS Excel.- Rīga: Datorzinību centrs, 2003. 354 lpp.

Further reading

1. Zinātnisko publikāciju datu bāzes
2. Zinātnisko publikāciju žurnāli
3. Johnson R.A., Wichern D.W. Applied Multivariate Statistical Analysis, 6th ed. USA: Pearson Education, Inc., 2007. 773 p.

Periodicals and other sources

1. The Official Journal of the International Association for Statistical Computing "Computational Statistics & Data Analysis". ISSN 0167-9473
2. The Journal of Modern Applied Statistical Methods. United States. ISSN 1538-9472
3. International Journal of Data Analysis Techniques and Strategies. IJDATS. ISSN 1755-8069

Notes

Compulsory study course in full-time and part-time studies of MF professional higher education bachelor study programs "Woodworking" and "Forest Engineer".