Veidlapa Nr. M-3 (8)

Course Description Status: Approved

Course Description Version: 25/26.R.1.00

Description Period: 2025./26 academic year rudens semestris

Study Course Accepted: -

Study Course Description

Methods of Mathematical Statistics in Health Sciences I

Main Study Course Information

Course Code
SL_043
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Medicine; Pharmacy
LQF
Level 8
Study Type And Form
Full-Time

Study Course Implementer

Course Supervisor
Māra Grēve
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 provide knowledge of the basic concepts of statistics; create awareness of the role of evidence-based medicine in health care.

Preliminary Knowledge

Knowledge of mathematics and informatics is required.

Learning Outcomes

Knowledge

1.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

1.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.

Competences

1.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.

Assessment

Individual work

Title
% from total grade
Grade
1.

Individual 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.

Examination

Title
% from total grade
Grade
1.

Examination
-
-
Solved practical tasks, working individually or in groups (100%).

Study Course Theme Plan

FULL-TIME
Part 1

  1. Lecture

Modality
Location
Contact hours
On site
Auditorium
2

Topics

The role of statistics in the research process. Descriptive statistics and inferential statistics. Testing statistical hypothesis with P-value and confidence intervals.
Description
Annotation: During the lecture students will gain an insight into the role of statistics in the research process, its classification and practical significance in health sciences. The main principles of hypothesis testing (P-value and confidence intervals) and misunderstandings that can result from interpretation of statistical tests will be discussed. Topics covered during the class: 1. The role of statistics in the research process in health sciences. 2. Significance of the descriptive statistics and inferential statistics in evidence-based medicine. 3. Principles of hypothesis testing. 4. Confidence intervals and possibilities of their use. Literature: 1. Petrie A. & Sabin C. Medical Statistics at a Glance, 4th edition, Wiley-Blackwell, 2019. ISBN: 978-1-119-16781-5 2. Greenland, 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.

  1. Lecture

Modality
Location
Contact hours
On site
Auditorium
2

Topics

Types of data and measurement scales. Normal distribution. Vast range of statistical methods.
Description
Annotation: During the lecture differences among different types of data and their measurement scales will be demonstrated. Attention will be paid to the necessity to check normal distribution of quantitative data. An insight will be gained into the variety of statistical data analysis methods and principles of test selections that depend on the measurement scale of the data and empirical distribution of quantitative data. Topics covered during the class: 1. Description of the data types and measurement scales, their differences in the process of statistical analysis of the data. 2. Role of the normal distribution in the data analysis and possibilities of its detection. 3. Insight into the variety of the methods for estimating relationships in data. Literature: 1. Petrie A. & Sabin C. Medical Statistics at a Glance, 4th edition, Wiley-Blackwell, 2019. ISBN: 978-1-119-16781-5 2. Field A. Discovering Statistics using IBM SPSS Statistics, 4th edition, Sage Publications, 2013. ISBN-13: 978-1446249185 3. Koo, T. K. and 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

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
3

Topics

Preparing data for Jamovi program. Descriptive statistics, one sample statistical tests
Description
Annotation: This class will be dedicated to the improvement of the skills in the use of IBM SPSS Statistics for data preparation for analysis, data description, visualization and analysis of the qualitative data. Attention will be paid to the selection of the correct test depending on the number of samples (one and two sample tests) and characteristics (dependent and independent tests). Topics covered during the class: 1. Data preparation for analysis in IBM SPSS Statistics. 2. Descriptive statistics for qualitative data. 3. One sample Chi square test, Two independent samples Chi square test and Fisher’s exact test. 4. McNemar’s test. Literature: 1. Peat J. & Barton B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal, 2nd edition, John Wiley & Sons, 2014. ISBN-13: 978-1118589939 2. Andrade, 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.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
3

Topics

Statistical tests for independent observations (parametric and nonparametric tests).
Description
Annotation: This class will be dedicated to the improvement of practical skills in analysis of quantitative data and data in an ordinal scale: description, visualisation and estimation of differences in groups using parametric and nonparametric tests. Differences between parametric and nonparametric tests, test selection depending on the number of groups (tests for one, two and more than two samples) and characteristics (dependent and independent sample tests) will be discussed. Topics covered during the class: 1. Selection of descriptive statistics for quantitative data and data in an ordinal scale. 2. Differences between parametric and nonparametric tests. 3. T-tests and one-way ANOVA. 4. Mann-Whitney test, Wilcoxon test, Kruskal-Wallis test. 5. Construction of diagrams for quantitative data and data in ordinal scale. Literature: 1. Peat J. & Barton B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal, 2nd edition, John Wiley & Sons, 2014. ISBN-13: 978-1118589939 2. Field A. Discovering Statistics using IBM SPSS Statistics, 4th edition, Sage Publications, 2013. ISBN-13: 978-1446249185 3. Hopkins, 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 4. Nahm, 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

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
3

Topics

Statistical tests for dependent observations (parametric and nonparametric tests).
Description
Annotation: This class will be dedicated to the improvement of practical skills in the calculation of correlation coefficients (parametric Pearson and nonparametric Spearman correlation coefficients) and understanding of the principles of the regression analysis and possibilities of its use (simple and multiple regressions, linear and binary logistic regression). An insight will be gained into situations when calculation of Cronbach’s alpha is needed. Topics covered during the class: 1. The essence of correlation. Pearson and Spearman correlation coefficients. 2. Simple linear regression and multiple regression. 3. Advantages of binary logistic regression. 4. Cronbach’s alpha coefficient. Literature: 1. Field A. Discovering Statistics using IBM SPSS Statistics, 4th edition, Sage Publications, 2013. ISBN-13: 978-1446249185 2. Schober, P., Vetter, T. R. 2021. Linear Regression in Medical Research. Anesth Analg. 132(1):108-109. DOI: 10.1213/ANE.0000000000005206. 3. Schober, P., Vetter, T. R. 2021. Logistic Regression in Medical Research. Anesth Analg. 132(2):365-366. DOI: 10.1213/ANE.0000000000005247. 4. https://statistics.laerd.com/spss-tutorials/cronbachs-alpha-using-spss-statistics.php

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
3

Topics

Data analysis of student data or database data. Practical exercises, working in groups.
Description
Annotation: During this lecture an insight will be gained into principles of the sample size calculation and the structure of statistical data analysis method description in accordance with the requirements for the scientific publication. Within the practical work, a description of statistical methods that will be used in the doctoral thesis will be written in accordance with the research design, used measurement scales of variables and data analysis methods that are characteristic to the speciality. Topics covered during the class: 1. Examples of the sample size calculations. 2. Introduction to the statistical data analysis method descriptions in scientific publications. 3. Writing a description of statistical methods that will be used in the doctoral thesis according to the research design and measurement scales and the used variables. Literature: 1. Charan, J. and 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 2. Simpson, 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 3. Zinātniskās publikācijas specialitātē, atbilstoši plānotajai promocijas darba tēmai.
Total ECTS (Creditpoints):
3.00
Contact hours:
16 Academic Hours
Final Examination:
Exam

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. (pēdējais iznākušais izdevums)

3.

Field, A. Discovering Statistics using IBM SPSS Statistics. 4th edition, Sage Publications, 2024.

Additional Reading

1.

Simpson, 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.v68i4.1471Suitable for English stream

2.

Koo, 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.2016.02.012Suitable for English stream

3.

Greenland, 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.Suitable for English stream

4.

Andrade, 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.Suitable for English stream

5.

Hopkins, 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: 10.1177/2192568218782679Suitable for English stream

6.

Nahm, 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.2016.69.1.8Suitable for English stream

7.

Schober, P., Vetter, T. R. 2021. Linear Regression in Medical Research. Anesth Analg. 132(1):108-109. DOI: 10.1213/ANE.0000000000005206.Suitable for English stream

8.

Charan, 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: 10.4103/0253-7176.116232Suitable for English stream

Other Information Sources

1.

Laerd Statistics.Suitable for English stream