Data Analysis in Health Care (SL_039)
About Study Course
Objective
This module “Data analysis in health care” is subdivided into three sub-modules
1. Mathematics applied in health management
2. Types and processing of data in health care
3. Statistics and statistical tools applied in health management
Sub-Module: “Mathematics applied to health management”
This module aims to ensure students’ understanding of basic theoretical foundations of statistical data analysis and advantages and limitations of quantitative methods.
Sub-Module: “Types and processing of data in health care”
This module aims to familiarize students with the classification of data used in health care, available data sources and pre-processing of the data for quantitative analysis.
Sub-Module: “Statistics and statistical tools applied to health management”
This module aims to provide knowledge and skills in the most widely used descriptive and inferential statistics, regression and correlation analysis.
The teaching and learning activities for all 3 Sub-Modules will include presentations, lectures, case-studies, discussions and practical work.
Prerequisites
Secondary school knowledge in mathematics and informatics.
Learning outcomes
Upon successful completion of the module´s course the students will:
• demonstrate knowledge with the basic ideas of linear algebra including concepts of linear systems, independence, theory of matrices, linear transformations;
• know data types and data sources in health care;
• recognize terminology used in statistics and basic methods used in research publications;
• know commonly used data processing tools in MS Excel and IBM SPSS;
• know data processing criteria of various statistical methods;
• interpret correctly the most important statistical indicators.
The students will be able to:
• apply solution methods of linear system for various problems;
• input and edit data in computer programs MS Excel and IBM SPSS, identify data types and validate the data;
• prepare data for statistical analysis correctly;
• choose appropriate data processing methods, incl., will 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 programs for obtained results;
• describe obtained research results correctly.
Students will be able to:
• argue and make decisions about statistical data types, sources and processing methods;
• recognize the appropriate tools of calculus to solve applied problems;
• use appropriate statistical methods to achieve research aims, using computer programs MS Excel and IBM SPSS;
• practically use learned statistical methods to process research data.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Health Management, VVMeng | 3 | Master’s | Limited choice | Māra Grēve | |
| Health Management, VVM | 3 | Master’s | Limited choice | Māra Grēve |
