Statistical Methods of Data Processing in Psychology

Study Course Description

Course Description Statuss:Approved

Course Description Version:2.00

Study Course Accepted:03.10.2018 13:25:02

Study Course Information
Course Code:		SL_022		LQF level:		Level 6
Credit Points:		4.00		ECTS:		6.00
Branch of Science:		Mathematics; Theory of Probability and Mathematical Statistics		Target Audience:		Psychology
Study Course Supervisor
Course Supervisor:		Silva Seņkāne
Study Course Implementer
Structural Unit:		Statistics Unit
The Head of Structural Unit:
Contacts:		23 Kapselu street, 2nd floor, Riga, +371 67060897, statistikarsu[pnkts]lv, www.rsu.lv/statlab
Study Course Planning
Full-Time - Semester No.1
Lectures (count)		16	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		32
Classes (count)		16	Class Length (academic hours)		2	Total Contact Hours of Classes		32
Total Contact Hours								64
Study course description
Preliminary Knowledge:
General psychology, secondary level knowledge and mathematics and informatics.
Objective:
Introduction with basic data processing, statistical methods and its use, develop the ability to process and analyze the data obtained in a psychological research and interpret the results.
Topic Layout (Full-Time)
No.	Topic			Type of Implementation		Number	Venue
1	Psychological research. Types of research. Mathematical statistics use in psychology.			Lectures		1.00	auditorium
2	Workshop "Types of research and mathematical statistics use in psychology"			Classes		1.00	computer room
3	Data types, measures.			Lectures		1.00	auditorium
4	Data input and coding (IBM SPSS).			Classes		1.00	computer room
5	Data primary processing.			Lectures		1.00	auditorium
6	Data primary processing (IBM SPSS).			Classes		1.00	computer room
7	Empirical distribution, its statistical indicators and graphical representations.			Lectures		1.00	auditorium
8	Empirical distributions and their match to normal distribution (IBM SPSS).			Classes		1.00	computer room
9	Central tendency, variance, asymmetric and excess indicators.			Lectures		1.00	auditorium
10	Central tendency, variance, asymmetric and excess indicators calculation (IBM SPSS).			Classes		1.00	computer room
11	Population and sample (sample method and types, population parameter estimation).			Lectures		1.00	auditorium
12	Statistical hypothesis.			Lectures		1.00	auditorium
13	Parametric methods: t-test.			Lectures		1.00	auditorium
14	Stjudent`s t-test (IBM SPSS).			Classes		1.00	computer room
15	Parametric methods: analysis of variance (ANOVA).			Lectures		1.00	auditorium
16	Analysis of variance (ANOVA, IBM SPSS)			Classes		1.00	computer room
17	Non-parametric methods: Chi-Square test, Kolmogorov-Smirnov test			Lectures		1.00	auditorium
18	Chi-Square test, Kolmogorov-Smirnov test (SPSS)			Classes		1.00	computer room
19	Non-parametric methods: Manna-Whitneya test, Wilcoxon test, Kruskola-Valisa test			Lectures		1.00	auditorium
20	Manna-Whitneya test, Wilcoxon test, Kruskola-Valisa test (IBM SPSS)			Classes		1.00	computer room
21	Correlation analysis.			Lectures		1.00	auditorium
22	Correlation analysis (IBM SPSS)			Classes		1.00	computer room
23	Regression analysis.			Lectures		1.00	auditorium
24	Regression analysis (IBM SPSS).			Classes		1.00	computer room
25	Non-parametric correlation methods			Lectures		1.00	auditorium
26	Non-parametric connection research methods (IBM SPSS)			Classes		1.00	computer room
27	The meaning of factor analysis and use in psychology			Lectures		1.00	auditorium
28	Factor analysis (IBM SPSS)			Classes		1.00	computer room
29	Publication and presentation of research results			Lectures		1.00	auditorium
30	Workshop "Quantitative research and statistical data processing methods in scientific article"			Classes		1.00	computer room
31	Computerized final test "IBM SPSS program and its use in data processing in psychological research"			Classes		2.00	computer room
Assessment
Unaided Work:
Individual reading of given literature: preparation of presentation about one psychological research type; home works, connected to psychological field data processing, interpretation and presentation; preparing empirical article (quantitative research) presentation about statistical data processing methods.
Assessment Criteria:
For every missed lecture - summary has to be written using given literature (min. 1 A4 page). Successfully completed homework. Requirements: 1) Data processed correctly (calculated); 2) Data are correctly interpreted; 3) Data are correctly presented. Presentation on preparation of one type of psychological research Requirements: 1) Presentation prepared in PowerPoint program is presented orally at a seminar; 2) Presentation is prepared using the following scheme Authors of the research, title, journal; Type of research; The structure of the article and its relation to the type of research; The main purpose of the research, the theoretical basis and the main quotes. Preparation of empirical articles (quantitative research) presentations on statistical data processing methods Requirements: 1) Presentation prepared in PowerPoint program is presented orally at a seminar; 2) Presentation is prepared using the following scheme Authors of the article, title, journal; The main purpose of the research, the theoretical basis, methods, used data processing methods and their justification, main quotes. Successful completion of computerized final test "SPSS program and its application in data processing in psychological research" Requirements: 1) Correctly processed data, correctly selected data processing methods. 2) The results of the data obtained are correctly formatted in the Word program. 3) The results of the data processing are correctly interpreted, the conclusions are correctly formulated.
Final Examination (Full-Time):		Exam (Written)
Final Examination (Part-Time):
Learning Outcomes
Knowledge:		Students define mathematical statistics basic concepts, recognize the formulas, describe mathematical statistics techniques and methods, name and describe data analysis basic principles in program SPSS.
Skills:		Students can process data and analyze statistical indicators, make correct conclusions.
Competencies:		Students are able to decide the use of appropriate data processing methods in each situation impose to prove hypothesis or research question clarification.
Bibliography
No.	Reference
Required Reading
1	Metodiskie norādījumi kursa darbu un bakalaura darbu izstrādei psiholoģijas studentiem
2	Pētniecība: teorija un prakse. (2016) K. Mārtinsones, A. Piperes, D. Kamerādes zin. red. Rīga: RAKA.
3	Raščevska M., Kristapsone S. (2000). Statistika psiholoģijas pētījumos. Rīga: Izglītības soļi.
4	Leech, N.L., Barrett, K.C., & Morgan, G.A. (2008). SPSS for intermediate statistics: Use and interpretation. Third 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	British Journal of Mathematical and Statistical Psychology. http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)2044-8…
2	Choosing the Correct Statistical Test in SAS, STATA and SPSS. https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
3	How to choose a statistical test. http://www.graphpad.com/www/book/choose.htm
4	Selecting statistics. http://www.socialresearchmethods.net/selstat/ssstart.htm