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2019/2020  BA-BEBUO1010U  Statistics

English Title
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 European Business
Course coordinator
  • Jens Olav Dahlgaard - Department of International Economics, Governance and Business (EGB)
Main academic disciplines
  • Methodology and philosophy of science
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 24-06-2019

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
Prerequisites for registering for the exam (activities during the teaching period)
Number of compulsory activities which must be approved: 2
Compulsory home assignments
There will be a total of three compulsory activities consisting of short written exercises. Each student will have to hand in up to five pages for each mandatory.

Two out of three activities must be approved to qualify for the exam.

No further attempts to pass the mandatory activities will be provided before the ordinary exam. If a student has not had the required number of activities approved, the student will not be able to attend the ordinary exam.

Students who fail to qualify for the ordinary exam must before the retake submit a ten page paper, covering the substance of the required number of mandatory activities. Specific requirements are provided by the course coordinator. When the paper is approved by the course coordinator, the student may be registered for the retake.

After the hand-in students will receive general feedback on the compulsory assignments in the lectures.
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
  • Books (including translation dictionaries), compendiums and notes in paper format
The student will have access to
  • Advanced 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

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. Student 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 a statistical software program such as Stata or 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
Teacher facilitated student feedback in exercise classes and workshops.

Class based feedback on selected exercises and compulsory homework.
Student workload
Lectures 24 hours
Exercises 26 hours
Exam 4 hours
Preparation and homework 128 hours
Workshops 24 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 24-06-2019