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2024/2025  BA-BEBUO1010U  Statistics

English Title
Statistics

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory (also offered as elective)
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 European Business
Course coordinator
  • Lasse Tobberup - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Methodology and philosophy of science
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 07/06/2024

Relevant links

Learning objectives
  • Identify and delimit a given statistical problem including identification of necessary and sufficient information to perform a relevant statistical analysis.
  • Perform basic data manipulations with a given data material using statistical software.
  • Use graphical and numerical methods to summarize the most important tendencies and associations in a given data material using statistical software.
  • Justify the use of a given statistical method and evaluate the strengths and weaknesses of this compared to other methods.
  • Demonstrate an understanding of the basics of probability and use these to quantify the uncertainty that exist in a given data analysis.
  • Independently conclude based on a given statistical analysis, critically reflect on the validity and reliability of the results, and communicate these in a clear, correct, and non-technical language.
Examination
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 Limited aids, see the list below:
The student is allowed to bring
  • USB key for uploading of notes, books and compendiums in a non-executable format (no applications, application fragments, IT tools etc.)
  • Any calculator
  • In Paper format: Books (including translation dictionaries), compendiums and notes
The student will have access to
  • Advanced IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
The number of registered candidates for the make-up examination/re-take examination may warrant that it most appropriately be held as an oral examination. The programme office will inform the students if the make-up examination/re-take examination instead is held as an oral examination including a second examiner or external examiner.
Course content, structure and pedagogical approach

The course aims to prepare students to conduct quantitative data analysis. The focus is on the capacity to conduct independent analyses using different types of data material, to interpret their results, and to understand and evaluate the assumptions on which the analyses rest. 

 

The course consists of lectures, workshops and exercises. The lectures will have a teacher driven review of a focused part of the theoretical course content. Students will be involved through brief peer-to-peer discussions and class discussions.

 

The workshops and exercises will focus on applying the methods from the curriculum and lectures to solve data analytical problems. In addition to a focus on understanding and interpreting statistical methods, a key element will be the introduction to the statistical software program R. Since the purpose of the exercises is to facilitate that the students apply the methods to real data problems, a high degree of student involvement is expected. 

 

The exercise teacher will assist students in applying the methods and direct discussions and interpretations of results. 

 

The problem sets in the exercise will to the extent that it is possible rely on data that is relevant to European Business. 

 

Fulfilment of the learning objectives of the course will make the students able to evaluate an appropriately formulated research questions in for example a Bachelor's thesis using statistical methods.

Description of the teaching methods
Lectures, workshops, and exercises. Students are expected to take active part in both lectures and exercises. Especially the exercises will be centered around student involvement.

Students are strongly encourage not to bring their laptops to the lectures, but instead rely on pen and paper for taking notes, since research suggests that using laptops has a negative effect on learning outcomes.*

*Carter, Susan Payne, Kyle Greenberg, and Michael S. Walker. "The impact of computer usage on academic performance: Evidence from a randomized trial at the United States Military Academy." Economics of Education Review 56 (2017): 118-132.

Students are expected to bring a laptop to the exercises and workshops.
Feedback during the teaching period
Feedback and continuous learning is integrated in several aspects of the course:

- In the weekly exercise classes and workshops, students will work with problem sets to assure that they progress continuously at the same pace as the curriculum. These exercises and activities will have teacher-facilitated feedback, and student-teacher interactions as well as class-based problem solving.

- Optional homework assignments will be published to provide the students with an opportunity to assess their level, and to identify where they need to focus additional attention. The homework assignments furthermore serve as practice for the exam. Two or three optional homework assignments will be provided over the course of the semester. After the hand-in of the assignments, students will receive collective feedback during the lectures.
Student workload
Lectures 26 hours
Exercises 26 hours
Exam 4 hours
Preparation and homework 124 hours
Workshops 26 hours
Expected literature

The full curriculum will be announced in the Fall, but it will include:

 

Kosuke Imai (2017): Quantitative Social Science. Princeton University Press.

 

Carter, Susan Payne, Kyle Greenberg, and Michael S. Walker. "The impact of computer usage on academic performance: Evidence from a randomized trial at the United States Military Academy." Economics of Education Review 56 (2017): 118-132.

 

Last updated on 07/06/2024