Skip to main content

Methods of Mathematical Statistics in Health Sciences I

Study Course Description

Course Description Statuss:Approved
Course Description Version:3.00
Study Course Accepted:30.04.2024 09:13:25
Study Course Information
Course Code:SL_043LQF level:Level 8
Credit Points:2.00ECTS:3.00
Branch of Science:Mathematics; Theory of Probability and Mathematical StatisticsTarget Audience:Medicine; Pharmacy
Study Course Supervisor
Course Supervisor:Māra Grēve
Study Course Implementer
Structural Unit:Statistics Unit
The Head of Structural Unit:
Contacts:14 Balozu street, Block A, Riga, +371 67060897, statistikaatrsu[pnkts]lv, www.rsu.lv/statlab
Study Course Planning
Full-Time - Semester No.1
Lectures (count)2Lecture Length (academic hours)2Total Contact Hours of Lectures4
Classes (count)4Class Length (academic hours)3Total Contact Hours of Classes12
Total Contact Hours16
Study course description
Preliminary Knowledge:
Knowledge of mathematics and informatics is required.
Objective:
To provide knowledge of the basic concepts of statistics; create awareness of the role of evidence-based medicine in health care.
Topic Layout (Full-Time)
No.TopicType of ImplementationNumberVenue
1The role of statistics in the research process. Descriptive statistics and inferential statistics. Testing statistical hypothesis with P-value and confidence intervals.Lectures1.00auditorium
2Types of data and measurement scales. Normal distribution. Vast range of statistical methods.Lectures1.00auditorium
3Preparing data for Jamovi program. Descriptive statistics, one sample statistical testsClasses1.00computer room
4Statistical tests for independent observations (parametric and nonparametric tests).Classes1.00computer room
5Statistical tests for dependent observations (parametric and nonparametric tests).Classes1.00computer room
6Data analysis of student data or database data. Practical exercises, working in groups.Classes1.00computer room
Assessment
Unaided Work:
1. Creating the table with names of variables, examples of data and their corresponding measurement scales of the current or planned research. 2. Reading literature from the list of Required reading according to topics of lectures and classes. 3. Reviewing examples of descriptions of statistical methods used in scientific publications.
Assessment Criteria:
Solved practical tasks, working individually or in groups (100%).
Final Examination (Full-Time):Exam
Final Examination (Part-Time):
Learning Outcomes
Knowledge:On successful completion of the study course, students will have knowledge that will allow to recognise the statistical terminology and the basic methods used in various publications.
Skills:Upon successful completion of the study course, students will be able to: • Correctly prepare and enter data in the Jamovi; • Create and edit tables and charts; • Select appropriate methods of data processing, incl. performing statistical hypotheses testing.
Competencies:On successful completion of the study course, students will be able to correctly interpret the most important statistical indicators and to use the acquired basic statistical methods in the study data processing.
Bibliography
No.Reference
Required Reading
1Petrie, A., Sabin, C. Medical Statistics at a Glance. 4th edition, Wiley-Blackwell, 2020.
2Peat, J., Barton, B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. 2nd edition, John Wiley & Sons, 2014.
3Field, A. Discovering Statistics using IBM SPSS Statistics. 4th edition, Sage Publications, 2018.
Additional Reading
1Simpson, S. H. 2015. Creating a Data Analysis Plan: What to Consider When Choosing Statistics for a Study. Canadian Journal of Hospital Pharmacy. 68(4): 311–317. DOI: 10.4212/cjhp.v68i4.1471
2Koo, T. K., Li, M. Y. 2016. A Guideline of Selecting and Reporting Intraclass Correlation coefficients for Reliability Research. Journal of Chiropractic Medicine. 15(2), 155–163. DOI: 10.1016/j.jcm.2016.02.012
3Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S., N., and Altman, D. G. 2016. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 31(4): 337-350. DOI: 10.1007/s10654-016-0149-3.
4Andrade, C. 2016. Understanding relative risk, odds ratio, and related terms: as simple as it can get. J. Clin Psychiatry. 76(7): 857-861. DOI: 10.4088/JCP.15f10150.
5Hopkins, S., Dettori, J. R., Chapman, J. R. 2018. Parametric and Nonparametric Tests in Spine Research: Why Do They Matter? Global Spine J. 8(6): 652–654. DOI: 10.1177/2192568218782679
6Nahm, F. S. 2016. Nonparametric statistical tests for the continuous data: the basic concept and the practical use. Korean J. Anesthesiol. 69(1): 8–14. DOI: 10.4097/kjae.2016.69.1.8
7Schober, P., Vetter, T. R. 2021. Linear Regression in Medical Research. Anesth Analg. 132(1):108-109. DOI: 10.1213/ANE.0000000000005206.
8Charan, J., Biswas, T. 2013. How to Calculate Sample Size for Different Study Designs in Medical Research? Indian J Psychol Med. 35(2): 121–126. DOI: 10.4103/0253-7176.116232
Other Information Sources
1Laerd Statistics. Available from: https://statistics.laerd.com/