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Methods of Quantitative Analysis
Study Course Description
Course Description Statuss:Approved
Course Description Version:8.00
Study Course Accepted:02.02.2024 12:31:01
| Study Course Information | |||||||||
| Course Code: | SBUEK_038 | LQF level: | Level 7 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Economics; Statistics | Target Audience: | Business Management; Marketing and Advertising | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Santa Bormane | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Faculty of Social Sciences | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Dzirciema street 16, Rīga, szf rsu[pnkts]lv | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 6 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 12 | ||||
| Classes (count) | 4 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 8 | ||||
| Total Contact Hours | 20 | ||||||||
| Part-Time - Semester No.1 | |||||||||
| Lectures (count) | 4 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 8 | ||||
| Classes (count) | 2 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 4 | ||||
| Total Contact Hours | 12 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Prior knowledge in mathematics, macroeconomics, and microeconomics. | ||||||||
| Objective: | To provide knowledge about commonly used quantitative methods for solving economic problems and basic skills in applying quantitative methods. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | The most important quantitative methods in economics | Lectures | 1.00 | auditorium | |||||
| 2 | The purpose of using quantitative methods | Lectures | 1.00 | auditorium | |||||
| 3 | The areas of using quantitative methods | Lectures | 1.00 | auditorium | |||||
| 4 | Concept of a model and economical mathematical models | Lectures | 1.00 | auditorium | |||||
| Classes | 2.00 | auditorium | |||||||
| 5 | Decision-making process and quantitative methods | Lectures | 1.00 | auditorium | |||||
| 6 | Use of quantitative methods in the decision-making process | Lectures | 1.00 | auditorium | |||||
| Classes | 2.00 | auditorium | |||||||
| Topic Layout (Part-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | The most important quantitative methods in economics | Lectures | 1.00 | auditorium | |||||
| 2 | The purpose of using quantitative methods | Lectures | 1.00 | auditorium | |||||
| 4 | Concept of a model and economical mathematical models | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 6 | Use of quantitative methods in the decision-making process | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| Assessment | |||||||||
| Unaided Work: | Students carry out independent work both in groups and individually – questionnaires are prepared on the topic of the Master’s thesis, presentations are made, work with literature is carried out – research and analysis, preparation for seminars and exam. | ||||||||
| Assessment Criteria: | Questionnaire according to the topic of the Master’s thesis, which shows the student’s ability to orientate in the information of the field (20%), assessment of presentations (30%), and assessment of the exam work (50%). | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | Exam (Written) | ||||||||
| Learning Outcomes | |||||||||
| Knowledge: | After the completion of the course, students gain knowledge and overview of methods of quantitative analysis and data processing, as well as use of these data in business, to make economically sound decisions. | ||||||||
| Skills: | After the completion of the course, students acquire skills to perform quantitative analysis and data processing in business under market conditions. | ||||||||
| Competencies: | After the completion of the course, students are able to practically apply the acquired knowledge on the use of quantitative analysis methods and data analysis. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Anderson, D. R. Quantitative methods for business, 2016 | ||||||||
| 2 | Wisniewski, M. Quantitative methods for decision makers, 2016 | ||||||||
| 3 | Curwin, J. Quantitative methods for business decisions, 2013 | ||||||||
| 4 | Stockemer, D. Quantitative Methods for the Social Sciences : A Practical Introduction with Examples in SPSS and Stata, 2019 | ||||||||
| 5 | Glyn, D. Quantitative methods for decision making using Excel, 2013 | ||||||||
| 6 | Orlovska, A. Ekonomiskā statistika, 2016 | ||||||||
| 7 | Hair, J. F., et al. Multivariate Data Analysis. Upper Saddle River, NJ [u.a.]. Pearson Prentice Hall, 2010. | ||||||||
| Additional Reading | |||||||||
| 1 | Blair J., Czaja R.F., Blair E. Designing Surveys: A Guide to Decisions and Procedures. Thousand Oaks, Calif, SAGE, 2014. | ||||||||
| 2 | Swift, L., Piff, S. Quantitative Methods for Business, Management and Finance. Hampshire: Palgrave Macmillan. 812p, 2010. | ||||||||
| 3 | Walters D.W., Walters D.J. Quantitative Methods for Business. Pearson Education, 2008. | ||||||||
| 4 | Croft T., Burton Gl., Myddelton D.R., Morris Cl., Barrow M. Quantitative Methods. 2004. | ||||||||
| 5 | Počs R. Kvantitatīvās metodes ekonomikā un vadīšanā. Rīga, RTU, 2003. | ||||||||
| 6 | Arhipova I., Bāliņa S. Statistika ekonomikā. Rīga, Datorzinību centrs, 2003. | ||||||||
| 7 | Kļaviņš D. Optimizācijas metodes ekonomikā I, II. Rīga, Datorzinību centrs, 2003. | ||||||||
| 8 | Goša Z. Statistika. Rīga, 2003. | ||||||||
| 9 | Burton Gl., Caroll G., Wall St. Quantitative Methods for Business and Economics. 2hd Ed., 2002. | ||||||||
