PhD Courses in Denmark

Course coordinators: Manuele Citi and Jan M. Bauer, Department of Management, Society and Communication (MSC)

Faculty
Associate Professor Manuele Citi 
Department of Management, Society and Communication, CBS

Associate Professor Jan M. Bauer
Department of Management, Society and Communication (MSC)

Prerequisites
Participants must be enrolled as PhD students in an institution of tertiary education. A precondition for receiving the course diploma is that the student attends the whole course (3 ECTS for 3 days or 5 ECTS for 3 days plus the 2 optional days).

The course does not assume a prior knowledge of statistics and does not have pre-requisites in terms of other PhD courses. The course only assumes a basic (undergraduate level) understanding of essential mathematical concepts.

Aim
This course helps qualitative-inclined PhD students to develop some fundamental quantitative analysis skills, using a user-friendly statistical software like Stata. The course is useful either for students who want to enrich their qualitative-oriented PhD thesis with some quantitative analysis, or for students who want to have a deeper understanding of some relevant empirical literature which based on quantitative methods. The course covers all the most fundamental topics of introductory statistics, teaches the appropriate analytical techniques for different types of data, and trains students to run their own analyses in Stata, both independently and in groups.

This course teaches students how to use specific statistical tools within a general empirical method that helps them to complement qualitative approaches. This will equip students with the skills to deal with the current and future challenges of conducting social science research at the doctoral and post-doctoral level.

Content

1.  An Introduction to the General Empirical Method

2. Types of variables and descriptive statistics

3. Introduction to Stata (enter data, clean data, writing procedures, data preparation)

4. Estimation and explanation of statistical models (t-tests, correlation analysis, simple linear regression, multiple regression)

5. Interpretation of results and critical reflection on their validity Class discussions and/or individual sessions on the application of quantitative methods to individual research questions

Teaching style
Lectures, discussions, and PC lab practicum workshops. The intended course runs (three) five days, combining morning and afternoon sessions.

Learning objectives
At the end of the course, doctoral students should be able to:

a. Specify the complementarities of qualitative and qualitative research within the general empirical method.
b. Know the quantitative approaches appropriate to their specific research interests.
c. Use statistical packages needed for their doctoral research needs.
d. Evidence a nuanced ability to consider empirical research questions.
e. Better understand empirical literature, with a view to improving critical reading ability, in order to g. suggest appropriate quantitative methods to address any range of research questions.

Lecture plan
Manuele Citi = MC; Jan M. Bauer = JMB

Exam
Not applicable.

Additional information
It is possible to choose the basic course with a duration of 3 days. An extension of 2 days is possible if you want to go beyond the absolute basics.

Additionally, we would like to offer an opportunity for participants to receive advisement on specific quantitative methods issues involving their research. A student who chooses this option would send a 10-page paper describing a concrete methodological issue s/he is dealing with, including possible approaches to solve the issue, with questions of interest or concern. The paper would have to be submitted no later than 6 weeks after the course. Feedback on the paper and specific questions presented would be provided in writing or conversation within a reasonable timeframe. Participants who wish to use this opportunity and engage in the arrangement are eligible to 1 ECTS extra

When registering, students need to decide whether to opt for 3 days, 5 days and whether to hand in a paper or not. 

ECTS
3 + 2 (Including add-on: + 1 ECTS). 

Course Literature
(A 2008) - Acock, Alan (2008). A Gentle Introduction to Stata. College Station: Stata Press. Pp. 189-206, 211-212.

(A+ 2019) - Amrhein et al. (2019) Scientists rise up against statistical significance. Available at: https://www.nature.com/articles/d41586-019-00857-9

(G 2017) - Gelman, Andrew (2017). Ethics and Statistics: Honesty and Transparency Are Not Enough. CHANCE, 30(1).

(I 2014) - Ioannidis, John (2014). How to Make More Published Research True. PLoS Medicine, 11(10).

(M&J 2017) - Mehmetoglu, Mehmet & Jakobsen, Tor Georg (2017). Applied Statistics using Stata – A Guide for the Social Sciences. SAGE, London

(W+2016) - Wicherts, Jelte M. et al. (2016) Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking. Frontiers in Psychology, 7: 1832.

Recommended additional literature
Greene, W.H. (2011). Econometric Analysis, 7th edition, Prentice Hall.

Wooldridge, J.M. (2008), “Introductory Econometrics: A Modern Approach, Thomson South- Western, 4th edition.

Weiers, R. (2007), “Introduction to Business Statistics,” Cengage Learning Services

Baum, C. (2006). An introduction to modern econometrics using Stata. College Station, TX: Stata Press.

Registration Deadline and Conditions
The registration deadline is 19 May 2025. If you wish to cancel your registration, it must be done by this date. By this deadline, we determine whether there are enough registrations to run the course or decide who should be offered a seat if we have received too many registrations.

If seats are still available, we will extend the registration deadline to fill the remaining spots. Once you receive our acceptance/welcome letter, your registration becomes binding, and no course fee refunds will be issued. The binding registration date is the deadline mentioned above.

Payment Methods 
Ensure you choose the correct payment method when finalizing your registration:

CBS students:
Select the payment method CBS PhD students. The course fee will be deducted from your PhD course budget.

Students from Other Danish Universities: 

Select the payment method Danish Electronic Invoice (EAN). Provide your EAN number, attention, and any relevant purchase (project) order number.

If you do not pay via EAN number, select Invoice to pay via electronic bank payment (+71).

Students from Foreign Universities:

Select the payment method Payment Card. If you are unable to pay by credit card, choose Invoice International to pay via bank transfer.