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2023/2024  KAN-CIBSO1061U  Applied Business Research

English Title
Applied Business Research

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for cand.merc. and GMA (CM)
Course coordinator
  • Clement Brebion - Department of Management, Society and Communication (MSC)
  • Manuele Citi - Department of Management, Society and Communication (MSC)
Main academic disciplines
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 01-06-2023

Relevant links
Learning objectives
At the end of the course you should be able to:
• Calculate and interpret summary and comparative measures of the data.
• Distinguish among different types of quantitative data (categorical, continuous, etc.) and recognize the types of information they provide and their limitations.
• Recognize the main types of distributions, how they relate to the nature of data at hand, and how to use them in statistical analysis.
• Draw inferences about population characteristics from samples.
• Recognize the key features of statistical testing (significance, power, confidence intervals) and conduct statistical tests on data.
• Understand the concepts of correlation, partial correlation, single- and multivariate regression, and conduct tests related to such regressions, including residual analysis.
• Generate and interpret the output from pre-developed software packages.
• Discuss and recommend solutions to problems encountered in the analysis of a specific phenomenon.
• Perform hypotheses testing of both simple and more composite hypotheses.
• Report and interpret the results of the analysis clearly and effectively to a reader who does not have a technical background in statistics and econometrics.
• Use longitudinal data for panel data regression.
• Make recommendations based upon the results of the analysis.
• Understand the assumptions of difference-in-difference estimation designs and randomized controlled experiments and interpret relevant outputs.
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
In order to qualify for the final exam, the students must get 1 out of 2 activities described below approved. All activities are individual. Further, they are independent, i.e., completion of one activity is not conditional on completion of the others.
1. Activity 1 – Problem Set 1
The students will receive a problem set consisting either of one long or two shorter problems, and the associated data set(s). They will be required to perform different types of statistical analyses and answer a set of questions based on the analyses. The deliverables include the R code to perform the analyses, the R output and a maximum 5 pages long document with answers to the questions.
2. Activity 2 – Problem Set 2
The students will receive a problem set consisting either of one long or two shorter problems, and the associated data set(s). They will be required to perform different types of statistical analyses and answer a set of questions based on the analyses. The deliverables include the R code to perform the analyses, the R output, and a maximum 5 pages long document with answers to the questions.
Students will not have extra opportunities to get the required number of compulsory activities approved prior to the ordinary exam. If a student has not received the approval of the required number of compulsory activities or has been ill, the student cannot participate in the ordinary exam.
If a student prior to the retake is still missing approval for the required number of compulsory activities and meets the pre-conditions set out in the program regulations, an extra assignment is possible.
The extra assignment is a 10-page home assignment that will cover the required number of compulsory activities. If approved, the student will be able to attend retake
Examination
Applied Business Research:
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.)
  • In Paper format: Books (including translation dictionaries), compendiums and notes
The student will have access to
  • basic 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.
Description of the exam procedure

 

 
Course content, structure and pedagogical approach

This course will introduce students to key methods of quantitative analysis that are widely applied in business and economic research. Topics covered include, among others, representing quantitative data, characterizing the data using numerical and graphic representations, performing tests and drawing inference from them, recognizing potential weaknesses and / or pitfalls of quantitative analysis, and using data for business decision making such as forecasting. The purpose of the course is to make students educated users of quantitative analysis by introducing the main theoretical concepts and issues rather than giving you extensive training in the underlying mathematical and statistical theory. The course emphasizes how to apply various statistical techniques in the support of decisions in the various functional areas of business and economics.
 
Description of the teaching methods
Teaching methods: The course consists of 12 lectures, plus 6 tutorials and an introductory session to R. A detailed plan of topics to be covered in each lecture, as well as respective readings for each topic, will be presented in the course syllabus to be made available before the start of the course. Lectures focus on presenting theory and insights, although numerical examples will be presented to help better understanding of theoretical concepts. On the other hand, tutorials focus exclusively on applying the concepts to concrete examples using real-world data. The tutorials also provide the hands-on experience to problem-solving.
Feedback during the teaching period
During the tutorial sessions, the instructor provides extensive feedback on the problem sets. Additionally, the lecturers provide feedback on small tasks to perform in class, and collective feedback on each one of the mandatory assignments.
Student workload
Lectures 36 hours
Exercises 24 hours
Introductory Session 3 hours
Preparation for classes and exam 170 hours
Expected literature

- Békés, G. and Kézdi, G. (2021), Data Analysis for Business, Economics and Policy, Cambridge University Press.

- Instructor PP slides and supplementary notes, if necessary.

- "Swirl" package in R for algorithm-led interactive learning.

 

 

 
Last updated on 01-06-2023