Veidlapa Nr. M-3 (8)
Study Course Description
Basics of Biostatistics
Course Code
SL_027
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Rehabilitation
LQF
Level 6
Study Type And Form
Full-Time; Part-Time
Study Course Implementer
Course Supervisor
Māra Grēve
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
To get basic skills in data processing methods. To emphasize understanding in choosing correct statistical methods and visualization. To emphasize statistics role in medical research and writing for publications.
Preliminary Knowledge
Secondary school background in mathematics and informatics.
Learning Outcomes
Knowledge
1.Upon successful acquisition of the course, the students will be able to: 1. Work in Excel and IBM SPSS to analyse data; 2. Formulate basic principles of data processing; 3. Interpret the main statistical terms in health sport speciality.
Skills
1.Upon successful acquisition of the course, the students will be able to: 1. Use MS Excel for their scientific work; 2. Make and use databases in Excel and IBM SPSS; 3. Conduct surveys for every topic in health sport speciality; 4. Collect data and correctly input them for data analysis; 5. Process data and analyse statistical indicators; 6. Make graphics in MS Excel and IBM SPSS.
Competences
1.Upon successful acquisition of the course, the students will be able to use correct statistics method in data analysis.
Assessment
Individual work
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Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
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-
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|
During the course students do individual work – perform calculations accordingly to given random tasks. Students can use their own data. Besides lectures, students have to study recommended literature and e-study materials, describe and interpret individuals work results in MS Word, Excel or IBM SPSS have to be used for calculations.
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Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
Students participation is evaluaded, individual work should be done either in Excel or IBM SPSS, results should be described in Word.
The final score consists of individual work (50%), written exam (50%).
For every missed lecture – a summary on the topic should be made (at least one paper, size A4).
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Study Course Theme Plan
FULL-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measure, data input, data preparation in MS Excel.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measure, data input, data preparation in MS Excel.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Basic actions in Excel and IBM SPSS
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics in Excel and SPSS
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics in Excel and SPSS
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: basic concepts, 2 group comparison (quantitative variable)
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: basic concepts, 2 group comparison (quantitative variable)
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: comparison of more than 2 groups (quantitative variable)
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: comparison of more than 2 groups (quantitative variable)
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: 2 and more group comparison (categorical outcome)
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: correlations, comparison of multiple quantitative and ordinal variable
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Inferential statistics: regression models
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data visualization
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data visualization
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Practical about statistical method representation in bachelor work
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Individual work. Exam
|
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)
PART-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measure, data input, data preparation in MS Excel.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics in Excel and SPSS
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data visualization
|
Total ECTS (Creditpoints):
3.00
Contact hours:
16 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Knapp H. Introductory statistics using SPSS. 2013
2.
Teibe U. Bioloģiskā statistika. Rīga: Latvijas Universitāte, 2007, 156 lpp.
Additional Reading
1.
Field A. Discovering Statistics using IBM SPSS Statistics. 5th edition, 2018.
2.
Petrie A. & Sabin C. Medical Statistics at a Glance. 4th edition, 2020.