Veidlapa Nr. M-3 (8)
Study Course Description
Methods of Mathematical Statistics in Health Sciences III
Course Code
SL_045
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Medicine; Pharmacy
LQF
Level 8
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Māra Grēve
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
14 Balozu street, Block A, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
To promote scientific capacity in the field of statistical analysis during the process of data exploration according to the planned research design of the doctoral thesis.
Preliminary Knowledge
Successfully completed course “Methods of Mathematical Statistics in Health Sciences II”.
Learning Outcomes
Knowledge
1.On successful completion of the study course, students will have knowledge that will allow to recognise procedures necessary for reliable statistical analysis of the data.
Skills
1.On successful completion of the study course, students will be able to plan and implement statistical analysis procedures for individual work with data.
Competences
1.On successful completion of the study course, students will be able to evaluate validity of the results of statistical analysis, write valid conclusions and participate in discussions about the statistical significance of the results.
Assessment
Individual work
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Title
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% from total grade
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Grade
|
|---|---|---|
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1.
Individual work |
-
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-
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1. Reviewing the choice of statistical methods used and interpretation of results reported in scientific publications.
2. Preparing data for analysis according to the planned research.
3. Confirming the choice of statistical methods used based in literature from the list of Required reading.
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Examination
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Title
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% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
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A written example of conclusion based on statistical analysis results (100%).
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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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On site
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Computer room
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4
|
Topics
|
Multivariate analysis of variance (MANOVA). Difference between one-way and two-way ANOVA
Description
Annotation: During the class students will analyse statistical methods used in scientific publications on the topic of doctoral thesis and will prepare data for analysis.
Topics covered during the class: 1. Analysis of statistical methods used in scientific publications on the topic of doctoral thesis.
2. Practical work: preparing data for analysis and exploring data.
Literature: Literature and scientific publications on the topic of doctoral thesis.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Mediation and moderation analysis.
Description
Annotation: During the class students will analyse statistical methods used in scientific publications on the topic of doctoral thesis, will choose appropriate methods for statistical analysis of data and will run tests.
Topics covered during the class: 1. Analysis of statistical methods used in scientific publications on the topic of doctoral thesis.
2. Practical work: selecting appropriate statistical methods and testing.
Literature: Literature and scientific publications on the topic of doctoral thesis.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Practical work. Statistical analysis of own research data or an example from different research designs.
Description
Annotation: During the class students will analyse statistical methods used in scientific publications on the topic of doctoral thesis, will run statistical tests for estimation of relationships in data, will summarize results and create diagrams for significant results.
Topics covered during the class: 1. Analysis of statistical methods used in scientific publications on the topic of doctoral thesis.
2. Practical work: running statistical tests for estimation of relationships in data, summarizing results and creating diagrams for significant results.
Literature: Literature and scientific publications on the topic of doctoral thesis.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Summary of learned statistical tests. Discussion of an actual data processing problem. Why is it important to plan data processing before the study begins?
Description
Annotation: During the class students will analyse statistical methods used in scientific publications on the topic of doctoral thesis, will run statistical tests for estimation of relationships in data, will perform in-depth analysis and write conclusions.
Topics covered during the class: 1. Analysis of statistical methods used in scientific publications on the topic of doctoral thesis.
2. Practical work: in-depth analysis and writing conclusions.
Literature: Literature and scientific publications on the topic of doctoral thesis.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
16 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Petrie, A., Sabin, C. Medical Statistics at a Glance. 4th edition, Wiley-Blackwell, 2020.Suitable for English stream
2.
Peat, J., Barton, B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. 2nd edition, John Wiley & Sons, 2014.Suitable for English stream
3.
Field, A. Discovering Statistics using IBM SPSS Statistics. 4th edition, Sage Publications, 2018.Suitable for English stream
4.
Torgo, L. Data Mining with R: Learning with Case Studies. 2nd edition. Chapman and Hall/CRC, 2020.Suitable for English stream
Additional Reading
1.
Tuncel, A., Atan, A. 2013. How to clearly articulate results and construct tables and figures in a scientific paper? Turkish Journal of Urology. 39 (Suppl 1): 16–19. DOI: 10.5152/tud.2013.048Suitable for English stream
Other Information Sources
1.
Laerd statistics.Suitable for English stream
2.
Praktiskā biometrija.Suitable for English stream