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2019/2020  BA-BMAKO1004U  Introduction to Statistics

English Title
Introduction to Statistics

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc in Business Administration and Market Dynamics and Cultutal Analysis
Course coordinator
  • Jan Michael Bauer - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 25-10-2019

Relevant links

Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • display an understanding of statistical terminology, processes and theories
  • use simple mathematical notation to express statistical problems
  • apply appropriate methods for the collection and analysis of quantitative data to solve a concrete problem
  • evaluate the use and interpretation of basic statistical methods
  • reflect upon issues regarding data privacy, methodological limitations and ethical considerations when conducting quantitative research
Introduction to Statistics:
Exam ECTS 7,5
Examination form Written sit-in exam on CBS' computers
Individual or group exam Individual exam
Assignment type Written assignment
Duration 4 hours
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Aids Open book: all written and electronic aids, including internet access
Read more here about which exam aids the students are allowed to bring and will be given access to : Exam aids and IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
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 targeted 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 the use of data collection and analytical software and acquire the ability to answer quantitative research questions using the appropriate technique. Methods of analysis are oriented towards consumer research and include the study of group differences, relationships and multivariate analysis, as well as an outlook towards move advanced methods.


Strengthening skills to read, critically assess and communicate the results of statistical analysis will enhance student’s 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.


The class will also cover the importance of data privacy and ethical research practices to ensure competent and responsible use of quantitative research methods.

Description of the teaching methods
The course will combine classical lectures, exercises and blended learning elements. With its focus on application and basic understanding, methods will be taught hands-on using software in class and exercises. Students will receive a proper introduction into the use of these tools. Participants are expected to actively engage into problem-solving exercises within class and home assignments, as well as pre-class preparation by reading the respective material. Continuous assessment will support student learning and provide guidance regarding their progress towards mastering the learning objectives.
Feedback during the teaching period
The course will contain a mid-term evaluation.
Student workload
Lectures+ Exercise 36 hours
Preparation+ Non-mandatory Assignments 166 hours
Exam 4 hours
Expected literature

To be provided

Last updated on 25-10-2019