Veidlapa Nr. M-3 (8)
Study Course Description
Research Data Processing
Course Code
SL_010
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Public Health
LQF
Level 6
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Vinita Cauce
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
23 Kapselu street, 2nd floor, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
Deepen knowledge and strengthen skills in mathematical data processing methods in the IBM SPSS program for the purposes of developing a bachelor's thesis and work in the public health specialty.
Preliminary Knowledge
Courses Mathematichal Statistics I and II should be successfully acquired before.
Learning Outcomes
Knowledge
1.Upon successful acquisition of the course, the students will be able to use Excel and IBM SPSS, Word for data processing, analysis, visualisation and formatting.
Skills
1.Upon successful acquisition of the course, the students will be able to: * perform data verification and prepare data for analysis; * filter data accordingly to different criteria; * transform files in IBM SPSS; * construct and edit tables and graphics in IBM SPSS and MS Excel; * correctly report data processing methods in MS Word; * write down activities in IBM SPSS syntax.
Competences
1.Upon successful acquisition of the course, the students will be able to use Excel and IBM SPSS, Word for data processing, analysis, visualisation and formatting.
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
|
-
|
|
Development of a draft of a bachelor's thesis, independent interpretation and description of the obtained results.
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
Active participation in practical classes.
Correctly designed thesis draft.
Examination, where theses draft will be evaluated: description of the statistical methods of the draft paper, the results part design (10%) and the results of the statistical analysis (chart design (30%), table design (30%) and text design (30%)).
|
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data input and exchange with MS Office and IBM SPSS.
Data file preparation. Data validation, cleaning (missing values and outliers).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data input and exchange with MS Office and IBM SPSS.
Data file preparation. Data validation, cleaning (missing values and outliers).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data visualising in tables (IBM SPSS, MS Excel). Interpretation of the results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data visualising in tables (IBM SPSS, MS Excel). Interpretation of the results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data visualising in graphs (IBM SPSS, MS Excel, EpiInfo). Interpretation of the results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data visualising in graphs (IBM SPSS, MS Excel, EpiInfo). Interpretation of the results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Confidence interval calculation (IBM SPSS, MS Excel, EpiInfo, etc.). Interpretation of the results.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Confidence interval calculation (IBM SPSS, MS Excel, EpiInfo, etc.). Interpretation of the results.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Teibe U. Bioloģiskā statistika, LU, 2007. (akceptējams izdevums)
2.
Petrie A. & Sabin C. Medical Statistics at a Glance. 2020.
Additional Reading
1.
Jenny V. Freeman, Stephen J. Walters, and Michael J. Campbell. How to Display Data, 2008
2.
Field A. Discovering Statistics using IBM SPSS Statistics. 2018