Veidlapa Nr. M-3 (8)
Study Course Description
Basics of Biostatistics
Course Code
SL_002
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Medicine
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Ieva Reine
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
23 Kapselu street, 2nd floor, Riga, statistika@rsu.lv, +371 67060897
About Study Course
Objective
To provide basic knowledge and skills in the planning of appropriate quantitative research, data mining and statistical data processing methods (descriptive statistics and inference statistics methods for the assessment of differences) necessary for the development of scientific research work and application of statistical indicators in their speciality.
Preliminary Knowledge
Secondary school level knowledge in Mathematics and Informatics.
Learning Outcomes
Knowledge
1.The aim of the course is to provide basic knowledge and skills in the planning of appropriate quantitative research, data mining, statistical data processing methods (descriptive statistics and inference statistics methods for the assessment of differences) necessary for the development of scientific research work and application of statistical indicators in their specialty. After completing the course, the students will have acquired the knowledge that will allow to: * choose the most appropriate data collection method; * recognise statistical terminology and basic methods used in various types of publications; * manually implement commonly used data analysis methods; * know the criteria for using data processing techniques; * correctly interpret the most important statistical indicators.
Skills
1.As a result of study course acquisition students will be able to: * choose appropriate data processing methods, including ability to perform statistical hypotheses testing; * statistically process research data; * correctly prepare data for statistical processing; * create tables and charts with the obtained results.
Competences
1.Upon completion of this course, students will be able to argument and make decisions about statistical data processing methods, use them to achieve research aims.
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
|
-
|
|
1. Individual work with the literature – prepare to lectures accordingly to the plan.
2. Individual data analysis.
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
2.
Examination |
-
|
-
|
|
Participation in practical lectures – individual work and active participation during the sessions. The practical application of the acquired statistical terms and methods – practical work (data analysis and interpretation of the results) at the end of the course (50 percent). On completion of this course – a multiple choice test with 25 theoretical questions in statistics (50 percent). Passed examination above 60 percent of both tasks together.
|
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
The role of statistics in the research process, an introduction to qualitative and quantitative research, data acquisition and analysis, descriptive statistics and methods of lock statistics; research methods in medical science, data mining methods: primary and secondary.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data collection: surveys, interviews, and document reviews – methods, advantages and disadvantages.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Research objectives and methodology selection. Components of a scientific project.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Research metdods in medical science, integrity of data mining, scientific credibility, quality criteria.
|
Total ECTS (Creditpoints):
1.50
Contact hours:
8 Academic Hours
Final Examination:
Test (Semester)
Part 2
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Sampling in primary data acquisition. Sampling errors. Analysis of non-parametric samples for quantitative data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data systematisation – descriptive statistics. Qualitative and quantitative variables. Statistical indicators.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Presentation of statistical data. Preparation and presentation of tables and charts, descriptive statistics, calculation of sample size.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Data distribution, statistical hypotheses, statistical significance, types of distribution testing.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Variation indicators, probability theory.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Presentation of practical work, exam.
|
Total ECTS (Creditpoints):
1.50
Contact hours:
24 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Sokal, R. R., Rohlf, F. J. J. Biometry: the principles and practice of statistics in biological research. 3rd edition. W.H. Freeman and Company, 2012 (akceptējams izdevums)Suitable for English stream
2.
Blettner, M., Heuer, C., Razum, O. Critical reading of epidemiological papers. A guide. Eur J Public Health. 2001;11:97–101. (akceptējams izdevums)Suitable for English stream
3.
Röhrig, B., du Prel, Jean-Baptist, Wachtlin, D., Blettner, M. Types of Study in Medical Research. Dtsch Arztebl Int. 2009 Apr; 106(15): 262–268. (akceptējams izdevums)Suitable for English stream
4.
Teibe, U. Bioloģiskā statistika. Rīga: LU Akadēmiskais apgāds, 2007, p 155. (akceptējams izdevums)
Additional Reading
1.
Campbell, M. J., Machin, D. Medical Statistics: A Textbook for the Health Sciences. 5th edition. John Wiley & Sons, 2021.Suitable for English stream
Other Information Sources
1.
Orlovska, A. Statistika: mācību grāmata. RTU izdevniecība, 2012, p 191.
2.
Dalgaard, P. Introductory Statistics with R. 2nd edition. Springer, New York, 2008. doi:10.1007/978-0-387-79054-1Suitable for English stream