Veidlapa Nr. M-3 (8)
Study Course Description
Biostatistics
Course Code
SL_003
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
6.00
Target Audience
Life Science
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Māra Grēve
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
Balozu Street 14 A, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
To acquire knowledge and skills in the statistical data processing methods used in biomedicine (descriptive statistics, inferential statistics for assessing differences and exploring relationships between different variables), which are necessary for the development of a scientific research thesis at Master's level, for an in-depth analysis of scientific publications and for the correct recording of the results of quantitative research.
Preliminary Knowledge
Knowledge in mathematics and informatics corresponding to the level of secondary education. Basic knowledge of statistics and research design is preferred.
Learning Outcomes
Knowledge
1.Recognise statistical terminology and basic methods used in scientific publications.
Individual work and tests
Individual work with Literature • Self-assessment tests • Test 1 • Test 2 • Publication analysis
2.Understand the basic functionality of MS Excel and IBM SPSS Statistcs and their practical applications in data processing.
Individual work and tests
Create a table • Data analysis
3.To understand the criteria for selecting data processing methods in accordance with the data structure and the aims of the research.
Individual work and tests
Data analysis • Self-assessment tests • Create a table • Test 1 • Test 2 • Publication analysis
4.Understand the importance of key statistical indicators and the principles of interpretation.
Individual work and tests
Publication analysis • Self-assessment tests • Test 2 • Create a table • Test 1 • Data analysis • Individual work with Literature
Skills
1.Enter and edit data in MS Excel and IBM SPSS Statistics.
Individual work and tests
Data analysis
2.Prepare data for statistical analysis in accordance with data quality requirements.
Individual work and tests
Data analysis
3.To identify and justify suitable statistical methods and conduct hypothesis testing.
Individual work and tests
Data analysis • Self-assessment tests • Create a table • Publication analysis
4.Perform statistical analyses of research data using MS Excel and IBM SPSS Statistics.
Individual work and tests
Create a table • Data analysis
5.Create tables and charts for results, using MS Excel and IBM SPSS Statistics programs.
Individual work and tests
Create a table
6.To provide structured and correct interpretations of statistical analysis results.
Individual work and tests
Test 2 • Test 1 • Data analysis • Publication analysis
Competences
1.To evaluate statistical methods and justify their use for a particular research purpose.
Individual work and tests
Self-assessment tests • Test 1 • Data analysis • Create a table • Publication analysis • Test 2
2.To apply and integrate the acquired methods in practical data analysis using MS Excel and IBM SPSS Statistics.
Individual work and tests
Create a table • Data analysis
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work with Literature |
-
|
-
|
|
Preparation for each class according to the thematic plan using presentations and compulsory literature. |
||
|
2.
Self-assessment tests |
5.00% from total grade
|
10 points
|
|
Nine self-assessment tests accompanying each new theoretical topic, designed to help students monitor and strengthen their understanding with no restrictions on completion time or the number of attempts. |
||
|
3.
Create a table |
-
|
Test
|
|
An independent assignment involving the creation of a publication‑ready table for comparing two independent groups. The student will receive a dataset (containing various types of variables), which must be analysed using previously learned methods, and the results compiled in a table following the given example. |
||
|
4.
Publication analysis |
5.00% from total grade
|
10 points
|
|
Independent analysis of a scientific publication: the student is required to find a full-text publication (from reputable scientific sources) on a biomedical topic of personal interest that employs one of the statistical data analysis methods taught in the course, deliver a presentation on it, and engage in a discussion of the publications chosen by classmates. |
||
|
5.
Course evaluation questionnaire |
-
|
-
|
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Data analysis |
50.00% from total grade
|
10 points
|
|
Research data files (or the student’s own research data) will be provided together with clearly defined research tasks. The student must analyse the data using descriptive and inferential statistical techniques, present and interpret the results in a final report, format the work according to the required standards, and submit it through the e‑studies. |
||
|
2.
Test 1 |
20.00% from total grade
|
10 points
|
|
Multi-choice test on the topics of the first part of the course (15 theoretical and practical questions in statistics with a time limit of 15 minutes). |
||
|
3.
Test 2 |
20.00% from total grade
|
10 points
|
|
Multi-choice test on the topics of the second part of the course (15 theoretical and practical questions in statistics with a time limit of 15 minutes). |
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measuring scales, data entry, data preparation in MS Excel.
Introduction to IBM SPSS Statistics. Basic operations with data in IBM SPSS Statistics. Calculation and graphical representation of frequency distributions.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Indicators of descriptive statistics in MS Excel and IBM SPSS Statistics, their graphical representation.
Normal distribution and its characteristic descriptive statistics indicators.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Confidence intervals. Statistical hypotheses, their types. Hypothesis testing. P value. Normal distribution test tests for IBM SPSS Statistics. One sample t-test in Ms Excel and IBM SPSS Statistics. Sample size calculation.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Parametric and non-parametric data processing methods. Comparison of independent and dependent samples for two groups.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Parametric and non-parametric data processing methods. Comparing independent and dependent samples for more than two groups.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Qualitative data processing methods for independent and dependent samples. Independent work: summary of a comparison of two independent groups.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Correlation analysis and linear regression analysis.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Binary logistic regression. ROC curves.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Survival analysis (Kaplan-Meier method and Cox regression).
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Bland-Altman diagram. Interclass correlation coefficient. Summary and practical application of the statistical methods learned.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Independent work: analysis of scientific publications.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Independent work with data in IBM SPSS Statistics. Presentation of independent work.
|
Total ECTS (Creditpoints):
6.00
Contact hours:
48 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Petrie, A. & Sabin, C. Medical Statistics at a Glance. 4th edition, Wiley-Blackwell, 2020.
2.
Peat, J. & Barton, B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. 2nd edition, John Wiley & Sons, 2014.
3.
Field, A. Discovering Statistics using IBM SPSS Statistics. 5th edition, Sage Publications, 2018.
Additional Reading
1.
Grech, V. Write a Scientific Paper (WASP): Effective graphs and tables. Early Human Development, 2019. DOI: 10.1016/j.earlhumdev.2019.05.013