Veidlapa Nr. M-3 (8)
Study Course Description
Processing of Research Data
Course Code
SL_023
Branch of Science
General Psychology; Psychology
ECTS
3.00
Target Audience
Psychology
LQF
Level 6
Study Type And Form
Full-Time; Part-Time
Study Course Implementer
Course Supervisor
Silva Seņkāne
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
Baložu iela 14, Block A, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
Develop knowledge, skills and competence in mathematical processing of research data to use statistical data processing methods in psychological research.
Preliminary Knowledge
The course “Statistical Data Research Processing Methods” completed.
Learning Outcomes
Knowledge
1.Student can name and describe basic principles of data analysis in IBM SPSS and MS Excel.
Skills
1.Student can input data for processing; process data independently and analyse statistical indicators.
Competences
1.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.
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual 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).
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
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.
|
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Types of scales, measurements and data. Basic principles of measurements.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data coding, input (MS Excel, IBM SPSS).
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Descriptive statistics.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics – IBM SPSS.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Inferential statistics.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics – IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics – IBM SPSS.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Data and their characteristic in the field of psychology, the most important methods of their processing.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Psychometric properties of scales (IBM SPSS).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Psychometric properties of scales (IBM SPSS).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Reading, describing and interpreting results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Presentation on individual research results.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
24 Academic Hours
Final Examination:
Exam (Written)
PART-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics – IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics – IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Psychometric properties of scales (IBM SPSS).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Psychometric properties of scales (IBM SPSS).
|
Total ECTS (Creditpoints):
3.00
Contact hours:
16 Academic Hours
Final Examination:
Exam (Written)
Bibliography
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.
Field, A., Van Doorn, J., & Wagenmakers, E. J. (2025). Discovering statistics using JASP. SAGE Publications Limited.
4.
Navarro, D. J., Foxcroft, D. R., & Faulkenberry, T. J. (2019). Learning statistics with JASP: A tutorial for psychology students and other beginners. Version12.
5.
Coolican, H. (2018). Research methods and statistics in psychology. Routledge.
Additional Reading
1.
Krastiņš, O., Ciemiņa, I. (2003). Statistika. Rīga: LR CSP.
2.
Krastiņš, O. (2003) Ekonometrija. Rīga: LR CSP.
Other Information Sources
1.
How to choose a statistical test.
2.
Selecting statistics.
3.
British Journal of Mathematical and Statistical Psychology.