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2022/2023  BA-BPOLO2201U  Advanced Topics in Quantitative Methods

English Title
Advanced Topics in Quantitative Methods

Course information

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 BSc/MSc i International Business and Politics, BSc
Course coordinator
  • Florian Hollenbach - Department of International Economics, Goverment and Business (EGB)
Main academic disciplines
  • Methodology and philosophy of science
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 24-06-2022

Relevant links

Learning objectives
  • Understand the theoretical assumptions behind statistical methods covered in the course
  • Be able to apply linear regression models and more advanced methods introduced in the course to problems in the social sciences and study of business
  • Understand and make use of analytical approaches to better understand human behavior in the political and business world
  • Ability to use the R software to undertake data visualization and statistical analysis of social science data
  • Ability to estimate and interpret advanced quantitative methods to answer important questions in the social sciences and study of business, in particular estimating causal effects
Course prerequisites
Students should have taken Quantitative Methods for Business and Social Science in the IBP Program
Prerequisites for registering for the exam (activities during the teaching period)
Number of compulsory activities which must be approved (see section 13 of the Programme Regulations): 1
Compulsory home assignments
The mandatory assignment is an individual 5 page written product on specific statistical analysis tasks analogous to the content of exercises. Approved/not approved will be granted based on the submitted written product. The assignment will be handed in around midway of the course.

The mandatory assignment must be approved for the student to participate in the final exam. Feedback on the assignment will be offered in class and during office hours (see below for more details).

If the mandatory assignment is not approved or there has been documented illness a second assignment will be offered before the ordinary exam takes place. This assignment will be an individual 5 page 72-hour take home assignment on set of statistical analysis tasks.

Please note that to submit the retake mandatory assignments it is a precondition that the student has made a valid attempt in the set activities, unless it can be documented that the lack of submission/participation was caused by illness or similar circumstances.
Advanced Topics in Quantitative Methods:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Written assignment
Duration 48 hours to prepare
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer
Make-up exam/re-exam
Same examination form as the ordinary exam
A new exam assignment must be answered. This applies to all students (failed, ill, or otherwise)
Description of the exam procedure

The exam is a take-home based on questions posed by the course instructor. The exam includes all material covered lectures, readings, and exercises.

Course content, structure and pedagogical approach

The course covers both the theoretical background and application of more advanced statistical and quantitative methods in business and social science. Upon completion of the course, students should have a theoretical understanding of the methods introduced and apply them to specific research problems. Building on the first 'Quantitative Methods for Business and Social Science' course in IBP, this course will first deepen students' theoretical understanding of multiple regression analysis. Next, the course will cover more advanced statistical methods and methods of causal inference, such as instrumental variables and panel data methods. The course consists of both lectures and applied exercises, in which we will actively work on implementing the methods covered in lectures. 
Please note: This course uses an applied approach and thus we will use software (R) to work with data throughout the whole course and in the examination.Beyond the software examples in the applied textbooks, students will receive a refresher to the software in the early stages of the course.

Description of the teaching methods
Lectures, exercise classes, some feedback session, and supporting video materials
Feedback during the teaching period
Students will receive in-class feedback on the mandatory activity, particularly about areas that need further study and work. Solutions for the mandatory activity will also be posted and subsequently discussed in detail in class or using a video format, including a walkthrough of the solution. In addition, we encourage you to ask questions or make comments in class and form self-study groups to secure peer feedback on your work. We will also use online forums to provide further discussion of the topics discussed in lectures and exercises. We will use office hours for specific inquiries, although these can never be a substitute for participation in lectures and classes.
Student workload
Preparation time (readings and coding for lectures, exercises, activities) 160 hours
Lectures, class exercises etc. 44 hours
Exam (actual exam period) 48 hours
Last updated on 24-06-2022