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

 

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.

Time/period	Faculty	Title	Readings
2 June 11.00 - 13.00	MC	Session 1: An overview of how quantitative studies can enrich qualitative research– introduction Group challenge 1
14:00 - 15.30	MC	Session 2: Introduction to Stata, descriptive statistics and graphs.	M&J (2017) Ch:1; 2.1-2.4.
15.45 - 17.00	MC, JMB	Session 3: Estimation and interpretation of descriptive statistics – hands on session
3 June 09.00 - 10.30	MC­	Session 4: Testing differences (e.g., t-tests)	M&J (2017) Ch: 2.5
10.45 - 12.15	MC, JMB	Session 5: Estimation and interpretation of testing differences (e.g., t-tests) – hands on session
13.15-15.00	JMB	Session 6: Explanation, estimation and interpretation of bivariate relationships: scatterplots and correlation analysis	A (2008)
15.30 - 17.30	JMB, MC	Session 7: Data handling in Stata - hands on session
4 June 09.00 – 10.30	JMB	Session 8: Regression analysis - OLS basics & bivariate	M&J (2017) Ch: 3
10.45 – 12.15	JMB	Session 9: Explanation of regression analysis - OLS multivariate & moderation effects	M&J (2017) Ch: 4, 5, 6
13.15 – 15.00	JMB, MC	Session 10: Estimation and interpretation of regression analyses – hands on session
15.30 – 17.00	JMB, MC	Session 11: Student presentations 1: Group challenge 1 and/or individual students’ projects.
2-days add-on
5 June 09.00: - 10.30	JMB	Session 12: OLS assumptions and extended methods	M&J (2017) Ch: 7, 9, 13
10.45 -12.15	JMB	Session 13: Advanced regression models - limited dependent variables (logit), multilevel analyses	M&J (2017) Ch: 8, 9, 10
13.15 – 15.00	JMB, MC	Session 14: Student presentations 2: Individual student project and presenting findings in a publishable regression table
15.30 – 17.00	JMB, MC	Session 15 Group challenge 2: Apply statistics to answer a specific research question
6 June 09.00 – 10.30	JMB, MC	Session 16: Group challenge 2: Finish research case and present results
10.45 – 12.15	JMB	Session 17: Critical discussion about statistical analyses: Robustness, Biases, and Errors.	(G 2017), (I 2014),  (A+ 2019), (W+ 2016)
13.15 – 15.00	JMB, MC	Session 18: Class discussions on the application of quantitative methods to individual research questions. Evaluation of the course

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.