Veidlapa Nr. M-3 (8)
Study Course Description
Research Methods in Rehabilitation II
Course Code
REK_209
Branch of Science
Clinical medicine; Sports Medicine and Rehabilitation
ECTS
3.00
Target Audience
Medical Services; Rehabilitation
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Signe Tomsone
Structure Unit Manager
Liāna Deklava
Structural Unit
Department of Rehabilitation
Contacts
Riga, 26a Anninmuizas boulevard, rk@rsu.lv, +371 20271291
About Study Course
Objective
The purpose of the course is to give students the opportunity to gain in-depth knowledge of statistical data processing methods (descriptive statistics, inferential statistics methods for evaluating differences and analytical statistics), which are necessary for the development of a final thesis, to develop skills in analyzing research results and to improve skills in presenting research results.
Preliminary Knowledge
Research planning and implementation methodology.
Learning Outcomes
Knowledge
1.The student will be able to recognize statistical terminology and methods used in various types of publications; is familiar with the possibilities of data processing offered by MS Excel and IBM SPSS; is familiar with the criteria for the use of data processing methods; correctly interpret the obtained research results.
Skills
1.The student will be able to correctly prepare data for statistical processing; to choose appropriate statistical data processing methods; to process research data using statistical data processing methods in Microsoft Excel and IBM SPSS Statistics computer programs; create tables and corresponding diagrams for the results obtained in Microsoft Excel and IBM SPSS Statistics computer programs; correctly describe the obtained research results.
Competences
1.The student will be able to make an argumentative decision on the use of statistical data processing methods to achieve the research goal and, using computer programs Microsoft Excel and IBM SPSS Statistics, to practically apply the acquired basic statistical methods in research data processing.
Assessment
Individual work
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Title
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% from total grade
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Grade
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|---|---|---|
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1.
Individual work |
-
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-
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Research data files will be prepared for each student (or the student can use his / her research data) with defined research tasks. The student will need to process the data to achieve the defined tasks using descriptive statistical methods, conclusion statistics and / or analytical statistical methods, describe the obtained results in the final work, design the work according to the requirements and present the obtained results in the last lesson.
In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal.
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Examination
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Title
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% from total grade
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Grade
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|---|---|---|
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1.
Examination |
-
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-
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Participation in practical classes and performance of planned tasks (60%), presentation of independent work (40%).
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Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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Off site
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E-Studies platform
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4
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Topics
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Descriptive statistics
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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Off site
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E-Studies platform
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4
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Topics
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Data analysis methods
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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Off site
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E-Studies platform
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4
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Topics
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Comparative analysis of parametric data
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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Off site
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E-Studies platform
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4
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Topics
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Correlation analysis
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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Off site
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E-Studies platform
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4
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Topics
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Regression analysis
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-
Class/Seminar
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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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Auditorium
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4
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Topics
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Presentation of research results
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Total ECTS (Creditpoints):
3.00
Contact hours:
24 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Practical Statistics for Medical Research By Douglas G. Altman, Boca Raton [etc.] : Chapman & Hall/CRC, 1999. (akceptējams izdevums)
2.
Pētniecības termiņu vārdnīca
Other Information Sources
1.
Elektroniskie informācijas resursi/ Electronic information resources