Course code Ekon2114

Credit points 2


Total Hours in Course80

Number of hours for lectures8

Number of hours for seminars and practical classes24

Independent study hours48

Date of course confirmation18.12.2018

Responsible UnitInstitute of Finance and Accounting

Course developer

author Finanšu un grāmatvedības institūts

Anda Vītiņa

Mg. paed.

Prior knowledge

Ekon1023, Microeconomics

Ekon2117, Macroeconomics

Course abstract

The course provides information on statistical theory, organization of statistical work in Latvia and the European Union. Students acquire practical skills in collecting, organizing, grouping and processing statistical information. Independent problem solving according to the topic, calculating various socio-economic statistical indicators and analysing the obtained results develop students’ analytical skills.

Learning outcomes and their assessment

Students will be able to:
1. Demonstrate the knowledge and understanding of the nature and concepts of statistical data, the ways of acquiring the data. Independent work.
2. Demonstrate the knowledge and understanding of how to apply statistical data and statistical methods in analysing the performance of enterprises and organisations. Independent assignments with calculations.
3. Demonstrate the knowledge of statistical indicators and how to apply them. Test with calculations.
4. Reasonably substantiate and interpret statistical indicators. Practical assignments.
5. Reasonably substantiate and explain data acquired in the result of observations and data grouping for the purpose of calculating various statistical indicators. Practical assignments.
6. Responsibly plan the completion of the assignments given, present the results of the research and calculations. Independent work.
7. Independently examine the development of various socio-economic phenomena and processes in time. Test with calculations.

8. Apply the statistical methods learnt and independently acquire necessary data at the enterprise/industry level, calculate statistical indicators as well as interpret the regularities identified. Examination.

Course Content(Calendar)

1. Organization of statistical work in Latvia. Statistical observation - data collection, methodological issues of observation. Lecture - 1 hour, practical work - 1 hour.
2. Statistical grouping, interpretation of results. Lecture - 2 hours, practical work - 2 hours
3. Designing of tables, graphical representation of data. Lecture - 1 hour, practical work - 1 hour.
4. Calculation of absolute and relative indicators. Lecture - 2 hours, practical work - 1 hour.
5. Measures of central tendency. Statistical distributions. Lecture - 2 hours, practical work - 2 hours.
6. Test work No.1. Test and exercises on topics: statistical subject, absolute and relative indicators. Measures of central tendency. 2 hours.
7. Measures of variation for ungrouped and grouped data. Lecture - 2 hours, practical work - 1 hour.
8. Time series. Investigation of seasonal fluctuations. Lecture - 2 hours, practical work - 2 hours.
9. Test work No.2. Test and exercises on the topic: time series. 2 hours.
10. Individual and aggregate indexes. Average indexes. Lecture - 2 hours, practical work - 1 hour.

11. Use of index method in business analysis. Lecture - 2 hours, practical work - 1 hour.

Requirements for awarding credit points

At the end of the course student must take an exam on the topics learned during the course.

Description of the organization and tasks of students’ independent work

To master and strengthen theory questions by studying literature and solving tasks. Prepare for tests and exam.

Criteria for Evaluating Learning Outcomes

1. Absolute and relative indicators. Measures of central tendency. Test with calculations. Weight 20%.
2. Time series analysis. Test with calculations. Weight 20%.
3. Practical assignments (on various topics). Calculations. Weight 10%.
4. Examination. All the topics. Weight 50%.

10% are equal to one point on a 10-point marking scale.

Compulsory reading

1. Goša Z. Statistika. Mācību grāmata. Rīga: Izglītības soļi, 2007. 327 lpp.
2. Orlovska A. Statistika. Mācību grāmata. Rīga: RTU, 2012. 191 lpp.
3. Orlovska A., Jurgelāne I. Ekonomiskā statistika. Rīga, RTU, 2016. 155 lpp.
4. Vergina G., Kārkliņa V. Statistika ekonomistiem. Rīga: Kamene, 2005. 92 lpp.
5. Ефимова М.Р. Статистика. Москва: Инфра-М, 2006. 335 c.
6. Рогатных Е.Б. Элементарная статистика. Москва: Экзамен, 2006. 158 с.

Further reading

1. Goša Z. Uzdevumu krājums statistikā. Rīga: Izglītības soļi, 2009. 116 lpp.
2. Statistikas likums. Pieejams:
3. Freedman D., Pisani R., Purves R., Adhikari A. Statistics. 2nd ed. New York; London: W.W.Norton and Co, 1991. 514 p.
4. Freedman D., Pisani R., Purves R. Statistics. New York; London: W.W.Norton and Co, 1980. 506 p.

Periodicals and other sources

1. CSP mājas lapa. Pieejams:
2. EM mājas lapa. Pieejams:
3. Finanšu un kapitāla tirgus komisija. Statistika. Pieejams:
4. Lursoft datu bāzes. Pieejams: http://
5. EUROSTAT datu bāzes un publikācijas. Pieejams:
6. Dienas Bizness: nedēļas laikraksts: ISSN 1407-2041
7. Latvijas Avīze: dienas laikraksts: ISSN 1407-3331


Field study course for the first level professional higher educational programme Business Studies