2025/2026 BA-BMAKO1041U Statistics
English Title | |
Statistics |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory |
Level | Bachelor |
Duration | One Semester |
Start time of the course | Spring |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
Study Board for Service and Markets
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 26-06-2025 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors:
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Examination | ||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||
This course provides an amicable introduction to the core concepts of statistics. Focusing on understanding and application, this course is accessible to students without a strong mathematical background. Starting from the basics of understanding and describing quantitative information and probabilities, the course will cover the essential aspects of statistics, such as sampling theory, statistical inference, and null-hypothesis testing. Students will learn to use analytical software and acquire the ability to answer quantitative research questions using the appropriate techniques. Methods of analysis are oriented towards consumer research and include the study of group differences, relationships, and multivariate analyses. Strengthening skills to read, evaluate, and communicate the results of statistical analyses will enhance students' ability to use quantitative data in a meaningful way. Students will become familiar with the use of basic mathematical notations and learn to solve simple problem sets linked to statistical questions. |
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Research-based teaching | ||||||||||||||||||||||||
CBS’ programmes and teaching are research-based. The following
types of research-based knowledge and research-like activities are
included in this course:
Research-based knowledge
Research-like activities
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Description of the teaching methods | ||||||||||||||||||||||||
The course will combine on-campus lectures and online material with supervised on-campus and online exercises. Blended learning elements will be used to foster student engagement and provide learning feedback. With its focus on application and basic understanding, methods will be taught hands-on using software in class and exercises. Students will receive an introduction to the use of the software R in dedicated workshops. Participants are expected to actively engage with the problem-solving exercises within class and at home, and pre-class preparation by reading the respective texts and following the online materials. Continuous assessment will support student learning and guide their progress towards mastering the learning objectives. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
Student receive feedback through exercises and dedicated blended learning elements. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||
Statistics: The Art and Science of Learning from Data, Global Edition by Alan Agresti & Christine A. Franklin & Bernhard Klingenberg 4th Edition, Pearson Education Limited 2018, ISBN: 9781292164779 |