Mathematical Statistics

Total Hours in Course120

Number of hours for lectures16

Number of hours for laboratory classes32

Date of course confirmation19.10.2011

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

prof.

Līga Paura

Dr. agr.

Course abstract

The aim of this course is to provide students with parametric and non parametric statistical methods, where as most software in social and economics science are based on statistical models. Statistical methods will be illustrated with real data examples. The course subjects are: parametric and nonparametric two independent samples tests, two related samples tests, ANOVA, nonparametric k independent samples and k related samples tests.

Learning outcomes and their assessment

depth knowledge and critical understanding about parametric and nonparametric data analysis methods; choose and apply methods according to research task; skills independently use statistical theory and choose parametric and nonparametric data analysis methods. Able to discuss about principles of choice the methods and their application and implementation of the specific problem at study; competence to realize data analysis in master work by using a data processing application software; to interpret the results and draw conclusions relate to the sector of the economy; to base decisions and to analyze them.

Compulsory reading

1. Arhipova I., Balina S. Statistika ekonomikā un biznesā. Risinājumi ar SPSS un MS Excel: mācību līdzeklis. Rīga: Datorzinību centrs, 2006. 359 lpp.
2. Goša Z. Statistika: mācību grāmata. Rīga: LU, 2003. 334 lpp.
3. Goša Z. Uzdevumu krājums statistikā. Rīga: LU, 2004. 93 lpp.
4. Krastiņš O., Ciemiņa I. Statistika: mācību grāmata. Rīga: LR Centrālā statistikas pārvalde, 2003. 267 lpp.

Atsauksmes