Basics of Biostatistics

Study Course Description

Course Description Statuss:Approved

Course Description Version:4.00

Study Course Accepted:06.09.2022 16:45:08

Study Course Information
Course Code:		SL_005		LQF level:		Level 5
Credit Points:		1.00		ECTS:		1.50
Branch of Science:		Mathematics; Theory of Probability and Mathematical Statistics		Target Audience:		Dentistry
Study Course Supervisor
Course Supervisor:		Maksims Zolovs
Study Course Implementer
Structural Unit:		Statistics Unit
The Head of Structural Unit:
Contacts:		14 Balozu street, Block A, Riga, +371 67060897, statistikarsu[pnkts]lv, www.rsu.lv/statlab
Study Course Planning
Full-Time - Semester No.1
Lectures (count)		0	Lecture Length (academic hours)		0	Total Contact Hours of Lectures		0
Classes (count)		6	Class Length (academic hours)		3	Total Contact Hours of Classes		18
Total Contact Hours								18
Study course description
Preliminary Knowledge:
Secondary school background in mathematics and informatics.
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.
Topic Layout (Full-Time)
No.	Topic			Type of Implementation		Number	Venue
1	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.			Classes		1.00	computer room
2	Descriptive statistics in IBM SPSS. Descriptive statistics of the Normal distribution.			Classes		1.00	computer room
3	Statistical hypothesis, types of statistical hypothesis. Hypothesis testing. P value.			Classes		1.00	computer room
4	Parametric statistics for quantitative data. Comparison of independent and dependent samples.			Classes		1.00	computer room
5	Nonparametric statistics for quantitative data. Comparison of independent and dependent samples.			Classes		1.00	computer room
6	Qualitative data processing. Independent and dependent samples.			Classes		1.00	computer room
Assessment
Unaided Work:
Individual work with the literature – prepare lectures accordingly to plan.
Assessment Criteria:
The final assessment consists of participation in practical classes with a theoretical test 50% and practical work 50%.
Final Examination (Full-Time):		Test
Final Examination (Part-Time):
Learning Outcomes
Knowledge:		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:		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.
Competencies:		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.
Bibliography
No.	Reference
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.