Course code Ekon2122

Credit points 6

Statistics

Total Hours in Course162

Number of hours for lectures32

Number of hours for seminars and practical classes32

Independent study hours98

Date of course confirmation25.09.2018

Responsible UnitInstitute of Economics and Finance

Course developer

author

Anda Vītiņa

Mg. paed.

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. Independently apply various statistical indicators. Test with calculations.
7. Responsibly plan the completion of the assignments given, present the results of the research and calculations. Individual presentation of the results of a study.

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. The subject of statistical science and theoretical foundations. Statistical methods and main stages of statistical analysis. Statistical observation - data collection, solving methodological issues of observation. Sampling methods.. Lecture - 3 hours, practical work - 2 hours.
2. Statistical grouping: selecting a grouping feature and determining the number of groups. Frequency distribution; absolute and relative frequencies. Charts of the frequency distribution. Lecture- 3 hours, practical work - 2 hours.
3. Test work No.1. Test and tasks on topics: statistical subject, data grouping, frequency distribution, graphical representation of the distribution. 1 hour
4. Absolute and relative indicators. Lecture - 4 hours, practical work - 3 hours.
5. Test work No.2. Absolute and relative indicators: calculations and interpretation. 2 hours
6. Measures of central tendency: arithmetic mean, median, mode. Lecture - 6 hours, practical work - 4 hours.
7. Test work No.3. Measures of central tendency: the theory test and calculations. 2 hours
8. Measures of variation: mean absolute deviation, variance, standard deviation, coefficient of variation. Measures of variation for ungrouped and grouped data. Skewness. Coefficient of asymmetry. Lecture- 6 hours, practical work - 4 hours.
9. Test work No.4. Measures of variation: the theory tests and calculations. 2 hours
10. Time series. Chain and base indicators. Average level indicator. Lecture 3 hours, practical work- 2 hours.
11. Time series. Methods of smoothing (forecasting). Investigation of seasonal fluctuations. Lecture - 4 hours, practical work - 2 hours.
12. Individual and aggregate indexes. Average indexes. Lecture - 3 hours, practical work - 2 hours.
13. Use of index method in business analysis. Practical work - 2 hours,
14. Test work No.5. Indexes. 2 hours.

Requirements for awarding credit points

At least 40% of the cumulative assessment must be obtained by passing the tests and the examination paper.

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. To develop independent work by performing statistical analysis of the activity of a chosen branch or enterprise.

Criteria for Evaluating Learning Outcomes

1. Statistical subject, data grouping, frequency distribution, graphical representation of the distribution Test with calculations. Weight 10%.
2. Absolute and relative indicators: calculations and interpretation. Test with calculations. Weight 10%.
3. Measures of central tendency. Test with calculations. Weight 10%.
4. Measures of variation. Test with calculations. Weight 10%.
5. Indexes. Test with calculations. Weight 10%.
6. Examination paper: Statistical analysis of the time line on basis of the performance of an industry or an enterprise (2-3 years period). Individual presentation of the results of a study. 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. Krastiņš O., Ciemiņa I. Statistika. Mācību grāmata augstskolām. –Rīga: LR CSP, 2003, 267 lpp.
5. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Rīga,Datorzinību centrs, 2006, 362 lpp.
6. Vergina G., Kārkliņa V. Statistika ekonomistiem. Rīga: Kamene, 2005, 92 lpp.
7. Graham A. Statistics. An Introduction. United Kingdom: Teach Yourself Books, 2017, 301 p.
8. Van Matre J.G., Gilbreath G.H. Statistics for Business and Economics, 3rd ed. - Homewood, IL: Irwin: 1987. BPI, xviii, 786 p.
9. Rowntree D. Statistics without Tears: an Introduction for Non-Mathematicians, United Kingdom : Penguin Books, 2018, 199 p.

Further reading

1. Goša Z. Uzdevumu krājums statistikā. Rīga: Izglītības soļi, 2009. 116 lpp.
2. Krastiņš O. Ekonometrija. Mācību grāmata augstskolām. Rīga: LR CSP, 2003. 207 lpp.
3. Krastiņš O. Varbūtību teorija un matemātiskā statistika. Rīga: Zvaigzne, 1985. 435 lpp.
4. Statistikas likums. Pieejams: https://likumi.lv/ta/id/274749-statistikas-likums
5. Freedman D., Pisani R., Purves R., Adhikari A. Statistics. 2nd ed. New York; London: W.W.Norton and Co, 1991. 514 p.
6. Freedman D., Pisani R., Purves R., Statistics. New York; London: W.W.Norton and Co, 1980. 506 p.

Periodicals and other sources

1. Oficiālais statistikas portāls. Pieejams: http://stat.gov.lv
2. EM mājas lapa. Pieejams: http://www.em.gov.lv
3. Finanšu un kapitāla tirgus komisija. Statistika. Pieejams: http://www.fktk.lv
4. Lursoft datu bāzes. Pieejams: http:// www.lursoft.lv
5. EUROSTAT datu bāzes un publikācijas. Pieejams: http://ec.europa.eu/eurostat
6. Dienas Bizness: nedēļas laikraksts: ISSN 1407-2041
7. Latvijas Avīze: dienas laikraksts: ISSN 1407-3331

Notes

Compulsory course for the Academic Bachelor Study Programme Economics. General study course for the Professional Bachelor’s Study Programme Entrepreneurship and Business Management.