Veidlapa Nr. M-3 (8)
Study Course Description
Analytical Statistical Methods in Psychological Research
Course Code
SL_026
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Psychology
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Diāna Kalniņa
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
To gain basic knowledge of data processing methods, to develop and use analytical statistical methods in psychological research.
Preliminary Knowledge
Bachelor's degree experience in research, appropriate Bachelor's degree knowledge in statistical methods.
Learning Outcomes
Knowledge
1.Students use statistical terminology; explain differences between univariate and multivariate statistical methods; can name and describe univariate and multivariate statistical data processing methods that can be used in different study designs.
Skills
1.Students have technological knowledge in SPSS to process research data, analyse statistical estimators; correctly describe results accordingly to given hypothesis or research question.
Competences
1.Students can professionaly deal with different psychological research tasks using computer, they use correct data processing methods accordingly to different study designs, analyse and interpet data processing results, formulate correct conclusions about research hypothesis results (accept or reject given hypothesis).
Assessment
Individual work
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Title
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% from total grade
|
Grade
|
|---|---|---|
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1.
Individual work |
-
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-
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Students independently read indicated literature. Independently do given data processing tasks (students are given data with fixed tasks in Excel, students do tasks, interpet results, work has to be submitted done in electronic format).
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Examination
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Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
(1) Fulfilled homework.
1. General population and sample.
2. Analysis of variance.
3. Regression analysis.
4. Component analysis. Factor analysis.
(2) Exam work – independent solution of individual task in SPSS program.
The final grade.
- For students who have submitted ALL assignments (four) and each has received a grade of at least 4 points, the final course grade will be the arithmetic mean of the assignment grades.
- For students who have not submitted ALL assignments or any assignment has received a grade lower than 4 points, a written exam must be taken. In this case, the final grade will consist of two components: the arithmetic mean of the assignment grades and the exam grade (in a 50:50 ratio).
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Study Course Theme Plan
FULL-TIME
Part 1
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Lecture
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
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Other
|
2
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Topics
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Research in psychology. Quantitative and qualitative research. General population and sample. Statistical methods and its applications. Data measurement scales and descriptive statistics. Inferential statistics.
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-
Class/Seminar
|
Modality
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Location
|
Contact hours
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|---|---|---|
|
On site
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Other
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2
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Topics
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One dimensional statistics – use of SPSS in data processing and analysis, presentation of results.
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-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Analysis of variance (ANOVA, MANOVA, MANCOVA, mixed design MANOVA).
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Analysis of variance – use of SPSS in data processing, analysis, presentation of results.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Regression analysis: standard, hierarchical, stepwise.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Regression analysis – use of IBM SPSS in data processing and analysis, presentation of results.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Insight into mediation and moderation analysis.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Component analysis and factor analysis. Confirmatory and exploratory factor analysis
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-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Factor extraction methods. Factor rotation methods.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Factor analysis – use of IBM SPSS in data processing and analysis, presentation of results.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Large scale assessment.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Large scale assessment – use of SPSS in data processing and analysis, presentation of results.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
24 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Pētniecība: teorija un prakse (2016). K. Mārtinsones, A. Piperes, D. Kamerādes redakcijā. Rīga: RAKA
2.
Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics 5th ed. SAGE
3.
Raščevska M. (2005). Psiholoģisko testu un aptauju konstruēšana un adaptācija. Rīga: Raka.
4.
Leech, N.L., Barrett, K.C., & Morgan, G.A. (2008). SPSS for intermediate statistics: Use and interpretation. 3rd ed. New York: London: Lawrence Erlbaum Associates.
Additional Reading
1.
Ievads pētniecībā: stratēģijas, dizaini, metodes. (2011). Sastādījusi K. Mārtinsone. Rīga: RAKA.
2.
Moore D. S. (2003). The basic practice of statistics. New York: W. H. Freeman & Company.
3.
Raščevska M., Kristapsone S. (2000). Statistika psiholoģijas pētījumos. Rīga: Izglītības soļi.
4.
Наследов А. Д. (2006). Математические методы психологического исследования. Анализ и интерпретация данных. СПб.: Речь.
5.
Сидоренко Е. (2001). Методы математической обработки в психологии. СПб.: Речь.
6.
Arhipova, I. Bāliņa, S. (2006). Statistika ekonomikā. Risinājumi ar SPSS un Microsoft Excel. Mācību līdzeklis 2. izdevums. Rīga: Datorzinību Centrs, - 364 lpp.
7.
Krastiņš O. (2003) Ekonometrija. Rīga: LR CSP.
8.
Krastiņš O., Ciemiņa I. (2003). Statistika. Rīga: LR CSP.
9.
Lasmanis, A., Kangro, I. (2004). Faktoru analīze. Rīga: Izglītības soļi.
Other Information Sources
1.
British Journal of Mathematical and Statistical Psychology. Available from: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)2044-8317
2.
Choosing the Correct Statistical Test in SAS, STATA and SPSS. Available from: http://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
3.
How to choose a statistical test. Available from: http://www.graphpad.com/www/book/choose.htm
4.
Selecting statistics. Available from: http://www.socialresearchmethods.net/selstat/ssstart.htm
5.
SPSS tutorials:
9.
Statistics tutorials. Available from: www.statsoft.com/textbook/stathome.html
10.
Metodiskie norādījumi maģistra darbu izstrādei RSU veselības psiholoģijas un supervīzjas studiju programmām. / K. Mārtinsone, V. Perepjolkina, J. Ļevina, J. Ļubenko, J. Koļesņikova, K. Vende, D. Kamerāde, J. I. Mihailovs, S. Silniece, J. Duhovska; V.
11.
Laerd Statistics: SPSS Statistics Tutorials and Statistical Guides