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About Study Course

Department: Statistics Unit
Credit points / ECTS:4 / 6
Course supervisor:Madara Miķelsone
Study type:Full time
Course level:Master's
Target audience:Nursing Science
Language:Latvian
Branch of science:Mathematics; Theory of Probability and Mathematical Statistics

Objective

Acquire in-depth knowledge and skills in statistical data processing methods (descriptive statistics, inferential statistical methods for estimating differences between various groups and analytical statistics), that are necessary for the processing of research data in the final thesis and in the chosen specialisation.

Prerequisites

Secondary school knowledge in mathematics and informatics.

Learning outcomes

Knowledge

Upon successful completion of the course, students’ knowledge will allow them to:
* recognise terminology used in statistics and inferential statistical methods used in different publications;
* know the most often used possibilities offered by MS Excel and IBM SPSS in data entry and processing;
* know the criteria for using data processing methods;
* interpret the most important statistical indicators correctly.

Skills

Having completed the course, students will be able to:
* input and edit data in computer programs MS Excel and IBM SPSS;
* prepare data for statistical analysis correctly;
* choose appropriate data processing methods, including statistical hypothesis testing using both basic inferential statistical methods and analytical statistical methods;
* process data in IBM SPSS;
* create and edit tables and graphs in MS Excel and IBM SPSS programs with the obtained results;
* describe the obtained research results precisely.

Competence

Upon successful acquisition of the course, students will be able to critically analyse and evaluate applied statistical methods in scientific publications, independently choose the appropriate inferential and analytical statistical methods in order to achieve the research aim and to apply in practice the learned inferential and analytical statistical methods by using IBM SPSS software.

Study course planning

Planning period:Year 2024, Spring semester
Study programmeStudy semesterProgram levelStudy course categoryLecturersSchedule
Nursing Studies, MZFM4Master’sRequiredEvija Nagle
Planning period:Year 2024, Autumn semester
Study programmeStudy semesterProgram levelStudy course categoryLecturersSchedule
Nursing Studies, MZFM3Master’sRequired