Processing of Research Data

Study Course Description

Course Description Statuss:Approved

Course Description Version:7.00

Study Course Accepted:17.06.2022 15:46:23

Study Course Information
Course Code:		SL_023		LQF level:		Level 6
Credit Points:		2.00		ECTS:		3.00
Branch of Science:		Psychology; General Psychology		Target Audience:		Psychology
Study Course Supervisor
Course Supervisor:		Silva Seņkāne
Study Course Implementer
Structural Unit:		Statistics Unit
The Head of Structural Unit:
Contacts:		Baložu iela 14, Block A, Riga, +371 67060897, statistikarsu[pnkts]lv, www.rsu.lv/statlab
Study Course Planning
Full-Time - Semester No.1
Lectures (count)		4	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		8
Classes (count)		8	Class Length (academic hours)		2	Total Contact Hours of Classes		16
Total Contact Hours								24
Part-Time - Semester No.1
Lectures (count)		2	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		4
Classes (count)		6	Class Length (academic hours)		2	Total Contact Hours of Classes		12
Total Contact Hours								16
Study course description
Preliminary Knowledge:
The course “Statistical Data Research Processing Methods” completed.
Objective:
Develop knowledge, skills and competence in mathematical processing of research data to use statistical data processing methods in psychological research.
Topic Layout (Full-Time)
No.	Topic			Type of Implementation		Number	Venue
1	Types of scales, measurements and data. Basic principles of measurements.			Lectures		1.00	auditorium
2	Data coding, input (MS Excel, IBM SPSS).			Classes		1.00	computer room
3	Descriptive statistics.			Lectures		1.00	auditorium
4	Descriptive statistics – IBM SPSS.			Classes		1.00	computer room
5	Inferential statistics.			Lectures		1.00	auditorium
6	Inferential statistics – IBM SPSS.			Classes		2.00	computer room
7	Data and their characteristic in the field of psychology, the most important methods of their processing.			Lectures		1.00	auditorium
8	Psychometric properties of scales (IBM SPSS).			Classes		2.00	computer room
9	Reading, describing and interpreting results.			Classes		1.00	computer room
10	Presentation on individual research results.			Classes		1.00	computer room
Topic Layout (Part-Time)
No.	Topic			Type of Implementation		Number	Venue
1	Types of scales, measurements and data. Basic principles of measurements.			Lectures		0.50	auditorium
2	Data coding, input (MS Excel, IBM SPSS).			Classes		0.50	computer room
3	Descriptive statistics.			Lectures		0.50	auditorium
4	Descriptive statistics – IBM SPSS.			Classes		0.50	computer room
5	Inferential statistics.			Lectures		0.50	auditorium
6	Inferential statistics – IBM SPSS.			Classes		2.00	computer room
7	Data and their characteristic in the field of psychology, the most important methods of their processing.			Lectures		0.50	auditorium
8	Psychometric properties of scales (IBM SPSS).			Classes		2.00	computer room
9	Reading, describing and interpreting results.			Classes		0.50	computer room
10	Presentation on individual research results.			Classes		0.50	computer room
Assessment
Unaided Work:
Individually strengthen the lecture material by systematically reading the literature; individual work related to the processing, interpretation and presentation of psychology field data (processing, interpretation and presentation of the Bachelor's Thesis data).
Assessment Criteria:
Independent work related to the processing, interpretation and presentation of psychology field data (processing, interpretation and presentation of the Bachelor's Thesis data). Requirements: 1) Correctly prepared database for the IBM SPSS program in the Bachelor's Thesis. 2) Appropriately selected data processing methods. 3) Correctly processed data. 4) Data processing results are properly formatted and described. 5) Conclusions are made correctly. 6) Presentation is prepared and given on the research results using the PowerPoint program.
Final Examination (Full-Time):		Exam (Written)
Final Examination (Part-Time):		Exam (Written)
Learning Outcomes
Knowledge:		Student can name and describe basic principles of data analysis in IBM SPSS and MS Excel.
Skills:		Student can input data for processing; process data independently and analyse statistical indicators.
Competencies:		The student makes the correct decision about the use of appropriate data processing methods in the given situation, correctly interprets the most important statistical indicators in the field of psychology, as well as describes and presents the research in MS Office programs MS Word and MS PowerPoint.
Bibliography
No.	Reference
Required Reading
1	Metodiskie norādījumi kursa un bakalaura darbu izstrādei psiholoģijas studentiem
2	Pētniecība: teorija un prakse. (2016). K. Mārtinsones, A.Piperes, D.Kamerādes red. Rīga: RAKA.
3	Leech, N.L., Barrett, K.C., & Morgan, G.A. (2008). SPSS for intermediate statistics: Use and interpretation. 3rd Edition. New York: London: Lawrence Erlbaum Associates.
Additional Reading
1	Krastiņš, O., Ciemiņa, I. (2003). Statistika. Rīga: LR CSP.
2	Krastiņš, O. (2003) Ekonometrija. Rīga: LR CSP.
3	Moore, D. S. (2003). The basic practice of statistics. New York: W. H. Freeman & Company.
4	Наследов, А.Д. (2006). Математические методы психологического исследования. Анализ и интерпретация данных. СПб.: Речь.
Other Information Sources
1	Choosing the Correct Statistical Test in SAS, STATA and SPSS. Available from: http://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
2	How to choose a statistical test. Available from: http://www.graphpad.com/www/book/choose.htm
3	Selecting statistics. Available from: http://www.socialresearchmethods.net/selstat/ssstart.htm
4	British Journal of Mathematical and Statistical Psychology. Available from: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)2044-8…