Veidlapa Nr. M-3 (8)
Study Course Description
Basics of Biostatistics
Course Code
SL_005
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
1.50
Target Audience
Dentistry
LQF
Level 5
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Maksims Zolovs
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 get basic knowledge in data processing methods (descriptive statistic, inferential statistic to estimate differences), that can be used in thesis work and in their speciality.
Preliminary Knowledge
Secondary school background 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; * to know IBM SPSS offered data processing tools; * to know data processing method criterias; * 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 program IBM SPSS; * to prepare data for statistical analysis correctly; * to choose appropriate data processing methods, incl., are able to do statistical hypothesis testing; * statistically analyse research data using computer program IBM SPSS; * create tables and graphs in IBM SPSS with obtained results; * precisely describe obtained research results.
Competences
1.After completion of this course, students will be able to argue and make decisions about statistical data processing methods, use them to achieve research aims, using computer program IBM SPSS, practically use learned statistical basic methods to process research data.
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
|
-
|
|
Individual work with the literature – prepare lectures accordingly to plan.
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
The final assessment consists of participation in practical classes with a theoretical test 50% and practical work 50%.
|
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
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. Basic actions with data in the IBM SPSS program.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
Topics
|
Descriptive statistics in IBM SPSS.
Descriptive statistics of the Normal distribution.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
Topics
|
Statistical hypothesis, types of statistical hypothesis.
Hypothesis testing. P value.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
Topics
|
Parametric statistics for quantitative data.
Comparison of independent and dependent samples.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
Topics
|
Nonparametric statistics for quantitative data.
Comparison of independent and dependent samples.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
3
|
Topics
|
Qualitative data processing. Independent and dependent samples.
|
Total ECTS (Creditpoints):
1.50
Contact hours:
18 Academic Hours
Final Examination:
Test
Bibliography
Required Reading
1.
Field A. Discovering Statistics using IBM SPSS Statistics. 4th edition, 2018.
2.
Teibe U. Bioloģiskā statistika. Rīga: Latvijas Universitāte, 2007, 156 lpp. (akceptējams izdevums)
3.
Petrie A. & Sabin C. Medical Statistics at a Glance. 3rd edition, 2020.