Course code Mate5011
Credit points 3
Data Processing Methods
Total Hours in Course81
Number of hours for lectures16
Number of hours for laboratory classes16
Independent study hours49
Date of course confirmation15.03.2011
Responsible UnitInstitute of Computer Systems and Data Science
Course developers
Līga Paura
Dr. agr.
Datoru sistēmu un datu zinātnes institūts
Laima Bērziņa
Dr. sc.ing.
Course abstract
The course gives introduction to the data manipulation, management and analysis in the different statistical software. The following topics are covered: descriptive statistics, graphical summarizing of data, correlation, ordinal correlations, Chi-square statistics and coefficients for relation analysis between nominal data. Also qualitative research methods are covered.
Learning outcomes and their assessment
Knowledge and critical understanding about data analysis methods; how to apply data analyses methods in social research projects; skills to discuss the choice of methods of data processing principles, their application and implementation, to interpret the results and draw conclusions; competences to use statistical software and realize data analysis outcomes in master work.
Compulsory reading
1. Arhipova I., Bāliņa S. Statistika ekonomikā: risinājumi ar SPSS un Microsoft Excel. Rīga: Datorzinību centrs, 2003. 349 lpp.
2. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Rīga: Datorzinību centrs, 2006. 362 lpp.
3. Paura L., Arhipova I. Statistiskās neparametriskās metodes. SPSS datorprogramma: mācību līdzeklis. Jelgava: LLKC, 2002. 148 lpp.
4. Kroplijs A., Raščevska M. Kvalitatīvās pētniecības metodes sociālajās zinātnēs. Rīga: Raka, 2004. 178 lpp.
Further reading
1. Miller R.L. et al. SPSS for social scientists. New York: Palgrave Macmillan, 2002. 334 lpp.
2. Strauss A., Corbin J. Basics of Qualitative Research. Los Angeles: CA Sage. 1998. 312 lpp.
3. Berg B.L. Qualitative research methods for the social sciences. Boston: Allyn & Bacon, 2007. 384 lpp.