Course type: elective
Lecturer: Irena Ograjenšek, Ph.D., Associate Professor
 

For the timeline see Curriculum.

Prerequisites:

• Enrolment into the relevant academic year.
• Positively graded seminar paper is a prerequisite for written exam.

Content (Syllabus outline):
Statistical quality control and business sciences: a historical perspective.
Modern quality management approaches:

• system
• model
• qualitative
• quantitative

Levels of analysis in statistical quality control:

• process
• products and services
• workplace
• department
• company

Data sources for statistical quality control.
Sampling for statistical quality control.
Tools and methods of statistical quality control:

• basic typologies
• selection and practical application of qualitative tools and methods
• selection and practical application of quantitative tools and methods
• statistical quality control in real time

Statistical quality control and statistical consulting.
Other relevant topics.

Objectives and competences:
The goal of the course is to introduce students to statistical quality control (SQC) emphasizing those aspects which are relevant for SQC's practical implementation.

Intended learning outcomes:
In-depth knowledge of theoretical and practical aspects of SQC.
Understanding of the link between SQC and business analysis / business planning.
Skills acquisition:

• secondary data search, evaluation and use in SQC processes;
• primary data collection, evaluation and use in SQC processes;
• use of statistical software packages in quality management processes;
• data/results of analysis visualization and dissemination in quality management processes.