Veidlapa Nr. M-3 (8)
Study Course Description
Biostatistics
Course Code
SL_006
Branch of Science
Other medical sciences
ECTS
3.00
Target Audience
Pharmacy
LQF
Level 7
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 knowledge and skills in data processing methods (descriptive statistics, inferential statistics methods to estimate differences and analytical statistics), to use in scientific work.
Preliminary Knowledge
Secondary school knowledge in mathematics and informatics.
Learning Outcomes
Knowledge
1.After completion of this course, students will demonstrate basic knowledge that allows to: * recognise terminology used in statistics and basic methods used in different publications; * know MS Excel and IBM SPSS offered data processing tools; * know data processing method criteria; * correctly interpret the most important statistical indicators.
Skills
1.After completion of this course, students will demonstrate skills: * to input and edit data in computer programs MS Excel and IBM SPSS; * to prepare data for statistical analysis correctly; * to choose appropriate data processing methods, incl., be able to do statistical hypothesis testing; * statistically analyse research data using computer programs MS Excel and IBM SPSS; * create tables and graphs in MS Excel and IBM SPSS programmes with obtained results; * describe obtained research results correctly.
Competences
1.After completion of this course, students will be able to argument and make decisions about statistical data processing methods, use them to achieve research aims, using computer programs MS Excel and IBM SPSS, practically use learned statistical basic methods to process research data.
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 analysis of scientific publication.
3. Individual work – every student will receive a research data file (or student can use their own) with previously defined research tasks. Student will statistically process data to reach defined tasks using descriptive statistic, inferential statistic and/or analytical statistics methods. As well as to report obtained results in final paper, using defined formatting style and to present obtained results in the last lecture.
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
10 points
|
|
Participation in practical classes. Examination of the practical application of the acquired statistical terms and methods. To get a successful grade: 1. Multichoice test about statistics – 50%; 2. Scientific publication analysis – 30%; 3. Individual work presentations – 20%. |
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measure, data input, data preparation in MS Excel.
Introduction to IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Descriptive statistics for quantitative and qualitative data.
Descriptive statistics of the Normal distribution.
Creation of tables and diagrams, correct design.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Hypothesis testing. Parametric and nonparametric tests for quantitative data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Hypothesis testing. Tests for qualitative data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Correlation and regression analysis.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Regression analysis. ROC curves.
|
|
Survival analysis.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Sample size estimation (including clinical trials).
Analysis of scientific publications.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Students presentations.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)
PART-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Introduction to statistics, the role of statistics in research process.
Data types, measure, data input, data preparation in MS Excel.
Introduction to IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Descriptive statistics for quantitative and qualitative data.
Descriptive statistics of the Normal distribution.
Creation of tables and diagrams, correct design.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Hypothesis testing. Parametric and nonparametric tests for quantitative data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Hypothesis testing. Tests for qualitative data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Correlation and regression analysis.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Regression analysis. ROC curves.
|
|
Survival analysis.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Sample size estimation (including clinical trials).
Analysis of scientific publications.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
4
|
Topics
|
Students presentations.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Teibe U. Bioloģiskā statistika. Rīga: Latvijas Universitāte, 2007, 156 lpp. (akceptējams izdevums)
2.
A. Field. Discovering Statistics using IBM SPSS Statistics. 5th edition, 2018.Suitable for English stream
3.
Petrie A. & Sabin Caroline. Medical Statistics at a Glance. Willey Blackwell, 2020.Suitable for English stream
Additional Reading
1.
Altman D. Practical Statistics for Medical Research. Chapman & Hall, 1997, pp. 612.Suitable for English stream
2.
Medical Statistics : A Guide to SPSS, Data Analysis and Critical Appraisal (2) by Barton, BelindaPeat, Jennifer, 2014Suitable for English stream