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2022/2023  AO-ASTHO1003U  Quantitative Research Methods in Tourism and Hospitality

English Title
Quantitative Research Methods in Tourism and Hospitality

Course information

Language English
Course ECTS 10 ECTS
Type Mandatory
Level Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
AO Study Board for cand.soc.
Course coordinator
  • Erik Braun - Department of Marketing (Marketing)
Main academic disciplines
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 16-06-2022

Relevant links

Learning objectives
This course teaches the students quantitative research methods that are relevant and used in the tourism and hospitality research. The specific learning objectives of the course are the following:
  • Students know how to assess the structure of the data and data quality
  • Students can analyse and work with different types of data
  • Students understand quantitative methods relevant for tourism–related research
  • Students can select the appropriate quantitative method for a research question
  • Students are able to apply quantitative methods for tourism–related research
  • Students are able to report and present the results of their quantitative analysis
Course prerequisites
There are no 'hard' course prerequisites for this course. Students are advised to view the online basic statistics refresher videos that are available in the summer.
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
Written group assignment, 10 pages.
Quantitative Research Methods in Tourism and Hospitality:
Exam ECTS 10
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance, see also the rules about examination forms in the programme regulations.
Individual or group exam Oral group exam based on written group product
Number of people in the group 2-3
Size of written product Max. 20 pages
Assignment type Written assignment
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

Aim of the course:

The purpose of this course is that students understand and can apply quantitative research methods that are relevant for and used in tourism and hospitality research.



Students learn how to screen data, assess the quality of the data and transformation the data (if needed). The main part of the lectures are dedicated that the students are equipped to understand and apply suitable quantitative methods for research questions and data types. This includes correlation analysis, A/B testing, regression analysis, factor analysis, moderation and mediation analysis and more advanced statistical methods. The course also includes a Hackathon with data of the tourism and hospitality industry. In the course, the students get data provided throughout the course to practice these methods as well as datasets to for their mid-term assessment and final written group project. Throughout the course, we will use R - the free software environment for statistical computing and graphics.


Description of the teaching methods
This course is delivered in a blended learning format. That is, the course combines physical in-class teaching with both prerecorded video as well as 'live' online teaching and tutorials.We are going to use a lot of online material in combination with an appropriate text book.
Feedback during the teaching period
Students will receive feedback in many ways: 1) in-class lectures; 2) in tutorials; 3) in group work and 4) during the office hours.
Student workload
Attending class 44 hours
Preparation 135 hours
Exam 96 hours
In total 275 hours
Expected literature

Preliminary literature:

- Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage publications.

- Supplemented by online materials on statistics with R


Last updated on 16-06-2022