Methods of Quantitative Analysis

Study Course Description

Course Description Statuss:Approved

Course Description Version:3.00

Study Course Accepted:17.06.2022 15:56:21

Study Course Information
Course Code:		SL_042		LQF level:		Level 7
Credit Points:		2.00		ECTS:		3.00
Branch of Science:		Economics; Statistics		Target Audience:		Business Management
Study Course Supervisor
Course Supervisor:		Diāna Kalniņa
Study Course Implementer
Structural Unit:		Statistics Unit
The Head of Structural Unit:
Contacts:		Riga, 14 Baložu iela, Block A, E-mail: statistikarsu[pnkts]lv, Phone: +37167060897
Study Course Planning
Full-Time - Semester No.1
Lectures (count)		2	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		4
Classes (count)		8	Class Length (academic hours)		2	Total Contact Hours of Classes		16
Total Contact Hours								20
Part-Time - Semester No.1
Lectures (count)		2	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		4
Classes (count)		5	Class Length (academic hours)		2	Total Contact Hours of Classes		10
Total Contact Hours								14
Study course description
Preliminary Knowledge:
Prior knowledge in mathematics and computer science.
Objective:
To provide knowledge about commonly used quantitative methods for solving economic problems and basic skills in applying quantitative methods. To acquire basic knowledge and skills in statistical data processing methods, which are necessary for the development of scientific research work and application of statistical indicators in specialty.
Topic Layout (Full-Time)
No.	Topic			Type of Implementation		Number	Venue
1	Types and methods of quantitative research. Their advantages and limitations. Primary, secondary and tertiary data. Scales.			Lectures		1.00	E-Studies platform
2	General population, target group and sample. Types of sampling and sampling principles. Data weighing. Accuracy and reliability of research results.			Classes		1.00	E-Studies platform
3	Concepts, operationalisation of concepts, study hypotheses. Preparation of research materials, types of questions.			Classes		2.00	E-Studies platform
4	Introduction to the IBM SPSS Statistical Data Processing Program. Basic operations with data in the IBM SPSS program (data entry, description, quality check). Practical file creation. Coding, creation of new variables.			Classes		2.00	E-Studies platform
5	Analysis of quantitative research data in IBM SPSS program, descriptive statistics.			Classes		1.00	E-Studies platform
6	Inferential statistics. Selection of an appropriate test.			Lectures		1.00	E-Studies platform
				Classes		2.00	E-Studies platform
Topic Layout (Part-Time)
No.	Topic			Type of Implementation		Number	Venue
1	Types and methods of quantitative research. Their advantages and limitations. Primary, secondary and tertiary data. Scales.			Lectures		1.00	E-Studies platform
2	General population, target group and sample. Types of sampling and sampling principles. Data weighing. Accuracy and reliability of research results.			Classes		1.00	E-Studies platform
3	Concepts, operationalisation of concepts, study hypotheses. Preparation of research materials, types of questions.			Classes		1.00	E-Studies platform
4	Introduction to the IBM SPSS Statistical Data Processing Program. Basic operations with data in the IBM SPSS program (data entry, description, quality check). Practical file creation. Coding, creation of new variables.			Classes		1.00	E-Studies platform
5	Analysis of quantitative research data in IBM SPSS program, descriptive statistics.			Classes		1.00	E-Studies platform
6	Inferential statistics. Selection of an appropriate test.			Lectures		1.00	E-Studies platform
				Classes		1.00	E-Studies platform
Assessment
Unaided Work:
Students study literature and e-study materials outside classes and lectures. Independent work is done both in groups and individually, homework is prepared, preparations for seminars and exam.
Assessment Criteria:
Attendance – 10%, tests – 40%, exam – 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, to be used in analszing research data and interpreting results.
Skills:		Students will acquire the skills to work with the statistical program SPSS, will learn to evaluate the accuracy and reliability of quantitative research results available in the public space, as well as to independently process quantitative research data, analyze statistical indicators and draw correct conclusions.
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	Pētniecība: teorija un prakse. (2016). K. Mārtinsones, A. Piperes, D. Kamerādes zin. red. Rīga: RAKA.
2	Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. 5th ed. SAGE
3	Hair, J. F., et al. (2010). Multivariate Data Analysis. Upper Saddle River, NJ [u.a.]. Pearson Prentice Hall.
4	Počs, R. (2003). Kvantitatīvās metodes ekonomikā un vadīšanā. Rīga, RTU.
Additional Reading
1	Walters D. W., Walters D. J. (2008). Quantitative Methods for Business. Pearson Education.
2	Curwin J., Slater, R. (2008). Quantitative Methods for Business Decisions.
3	Swift, L., Piff, S. (2010). Quantitative Methods for Business, Management and Finance. Hampshire: Palgrave Macmillan. 812p.
4	Blair, J., Czaja, R. F., Blair, E. (2014). Designing Surveys: A Guide to Decisions and Procedures. Thousand Oaks, Calif, SAGE.
Other Information Sources
1	Choosing the Correct Statistical Test in SAS, STATA and SPSS. http://stats.idre.ucla.edu/other/mult-pkg/whatstat/
2	Selecting Statistics. http://www.socialresearhmethods.net/selstat/ssstart.htm
3	We make statistics easy. The ultimate IBM® SPSS® Statistics guides. https://statistics.laerd.com/
4	Statistics tutorials. Available from: www.statsoft.com/textbook/stathome.html