Course code Mate1012
Credit points 3
Total Hours in Course81
Number of hours for lectures16
Number of hours for seminars and practical classes16
Independent study hours49
Date of course confirmation18.10.2021
Responsible UnitInstitute of Computer Systems and Data Science
Dr. sc.ing.
The study course provides an introduction to basic methods for studying social processes. After completing the course students acquire skills to analyse probability distributions, to apply descriptive statistics and to proceed time series analysis. The emphasis will be given on relationship analysis for continuous and categorical variables for understanding social processes.
Knowledge – about collection of social statistics data, classification of variables and basic methods for data analysis according to the research tasks (laboratory works). Skills – ability to carry out analyses with certain tasks of social processes research (laboratory works, tests). Competence – to analyse and systematize the results of data processing with critical insights in the context of assumptions and analysis results (independent work).
1. Introduction to social statistics methodology.
2. Sampling and measurement.
3. Probability distributions and graphical representations.
4. Descriptive statistics.
5. Time series analysis.
6. Correlation analysis for continuous data.
7. Linear regression.
8. Nonlinear regression.
9. Multiple regression.
10. Correlation analysis for non-continuous data.
11. Association analysis between categorical variables.
12. Analysis of population characteristics.
13. Territorial statistics.
14. Analysis of social processes – composition of households and budget surveys.
15. Analysis of social processes – education and employment.
16. Analysis of social processes – social security and health care.
Actual attendance of laboratory works;
representation of independent work results;
3 tests during the course.
During the semester student has to perform independent work, which provides analysis of certain social processes. The work must be written and submitted electronically on the e-learning site.
Presentation of the work should be given to the audience.
Cumulative course grade will be determined during the semester by the following basis with relative weights given:
attendance/participation in laboratory works – 10%;
independent work – 30%;
test Nr. 1 – 20%;
test Nr. 2 – 20%;
test Nr. 3 – 20%.
1. Orlovska A. Statistika. Mācību līdzeklis. Rīga: RTU, 2012. 191 lpp. 2. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Rīga: Datorzinību Centrs, 2006. 364 lpp.
2. Statistics for the behavioral sciences / Frederick J Gravetter, Larry B. Wallnau. Belmont, CA : Wadsworth/Thomson Learning, 2004. 746 p.
3. Sullivan M. Statistics : informed decisions using data. Upper Saddle River, N.J. : Prentice Hall is an imprint of Pearson, 2010. 788 p.
4. Lane D. Introduction to Statistics. E-book, 2003. Available: https://open.umn.edu/opentextbooks/textbooks/459
5. Illowsky B, Dean S. Introductory Statistics E-book, 2013. Available: https://openstax.org/details/books/introductory-statistics?Book%20details
1.Agresti A. Statistical Methods for the Social Sciences. Pearson, 2018. 576 p.
2.Aron A., Aron E., Coups E. Statistics for The Behavioral and Social Sciences. Harlow: Pearson Education, 2010. 504 p.
3.Levin J., Fox J., Forde R. Elementary Statistics in Social Research. Boston: Allyn & Bacon Pearson, 2010. 554 p.
4.Dietz T., Kalof L. Introduction to Social Statistics: The Logic of Statistical Reasoning. Wiley-Blackwell, 2009. 608 p.
Centrālās statistikas pārvaldes mājas lapa [tiešsaiste]. Pieejams: https://www.csb.gov.lv
Social Science Statistics [online]. Available: https://www.socscistatistics.com/
Official Statistics Portal [online] Available: https://stat.gov.lv/en
Eurostat [online] Available: https://ec.europa.eu/eurostat/web/main
FAOSTAT [online] Available: https://www.fao.org/faostat/en/#home
Academic study programme Sociology of Organizations and Public Administration.