1017874

Course
Applied Quantitative Methods for Non-quantitative Doctoral Researchers in Organization and Management Studies (3 days + 2 optional days) (Runs annually)

Faculty
Associate Professor Manuele Citi (Department of International Economics, Government and Business (CBS)
Associate Professor Jan Michael Bauer (Department of Management, Society and Communication, CBS)
Associate Professor Charles Tackney (Department of Management, Society and Communication, CBS)

Course Coordinator
Associate Professor Manuele Citi and Associate Professor Jan Michael Bauer

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 and 5 ECTS for 3 days plus the 2 optional days).

Doctoral students face a range of challenges concerning empirical methods. We first survey registered students to learn more about their particular research interests and perceived skilling needs, and adjust the specific quantitative methods content of the course to ensure instruction and practical application of appropriate quantitative research methods.

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.

Aim
This is an introductory course on quantitative methods for non-quantitative doctoral students, a course that allows qualitative scholars to get acquainted with the most fundamental tools for statistical analysis. The course has an approach that acknowledges the complementarity between qualitative and quantitative methods, and is based on a sequence of sessions that alternates theoretical insights and practical sessions. The students will use Stata in the hands-on sessions, learning the basics of coding in Stata at a pace that is comfortable for the whole class. This course prepares students to tackle the methodological challenges they may face in their doctoral research, providing skills that will remain useful and relevant for any post-doctoral career that involves organizational and management research.

Course content

Teaching style
Lectures, discussions and PC lab practicum workshops. Morning lecture and discussion sessions will be followed by afternoon PC lab and/or group work. C. Tackney will provide the initial lecture on General Empirical Method. Then we, M. Citi and J. Bauer, will work together to present specific statistics sessions. The intended course runs (three) five days, combining morning and afternoon sessions.

Lecture plan
Charles Tackney=CT; Manuele Citi=MC; Jan Michael Bauer=JMB

Time/period Faculty Title Readings
6 May
11.00 - 13.00 CT Session 1: An Overview of the place of quantitative studies in general empirical method L (2005)
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 Session 3: Estimation and interpretation of descriptive statistics – hands on session  
7 May
09.00 - 10.30 CT Session 4: A Session of Review and/or Remediation  
10.45 - 12.15 MC Session 5: Explanation of testing differences (t-tests) M&J (2017) Ch: 2.5
13.15 - 15.00 MC Session 6: Estimation and interpretation of testing differences (t-tests) – hands on session  
15.30 - 17.30 JMB Session 7: Explanation, estimation and interpretation of bivariate relationships: scatterplots and correlation analysis A (2008)
8 May
09.00 – 10.30 JMB Session 9: Explanation of regression analyses - OLS basics & bivariate M&J (2017) Ch: 3
10.45 - 12.15 JMB Session 10: Explanation of regression analyses - OLS multivariate & moderation effects M&J (2017) Ch: 4, 5, 6
13.15 - 15.00 JMB Session 11: Estimation and interpretation of regression analyses – hands on session  
15.30 - 17.00 JMB Session 8: Data handling in Stata - hands on session  
2-days add on
9 May
09.00 - 10.30 JMB Session 12: OLS assumptions and extended methods M&J (2017) Ch: 7, 9, 13
10.45 - 12.15 CT, JMB, MC Session 13: Class discussion and/or individual sessions on the application of quantitative methods to individual research questions. Presenting findings in a publishable regression table – hands on session.  
13.15 - 15.00 JMB Session 14: Advanced regression models - limited dependent variables (logit), multilevel analyses M&J (2017) Ch: 8, 9, 10
15.30 - 17.00 JMB, MC Session 15 Groups challenge 1: Apply methods to answer a specific research question  
10 May
09.00 - 10.30 JMB, MC Session 16: Groups 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), (G 2018), (I 2014)
13.15 - 15.00 CT, JMB, MC Session 18: Class discussions on the application of quantitative methods to individual research questions. Evaluation of the course  

Learning objectives
At the end of the course, doctoral students should be able to:
a. know and understand the historical and cultural contexts within which contemporary research methods function.
b. specify the complementarities of qualitative and qualitative research within the general empirical method.
c. know the quantitative approaches appropriate to their specific research interests.
d. use statistical packages needed for their doctoral research needs.
e. evidence a nuanced ability to consider empirical research questions in organizational and management studies, so they may
f. 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.

Exam
N/A

Other

Start date
06/05/2019

End date
10/05/2019

Level
PhD

ECTS
3 + 2 (Including add-on: + 1 ECTS). When registering, please decide whether to opt for 3 days, 5 days and whether to hand in a paper or not.

Language
English

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

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

• (G 2018) Gelman, Andrew (2018). The Failure of Null Hypothesis Significance Testing When Studying Incremental Changes, and What to Do About It. Personality and Social Psychology Bulletin, 44 (1).

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

• (L 2005) - Lonergan, Bernard J.F. (2005). Preface, pp. 3-9, Chapter 1, Elements, pp. 27- 31, and pp. 126-139 on the complementarity of classical and statistical heuristic structures. Insight: a Study of Human Understanding. Volume 3 of the Collected Works of Bernard Lonergan, (Frederik E. Crowe and Robert M. Doran, Eds.). Toronto: University of Toronto Press.

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

Recommended literature
• Agresti and Finlay (2008), Startistical Methods for the Social Sciences (4th ed.), Pearson.

• 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

Fee
DKK 3,900 (3 days) or 6,500 (5 days) + add-on DKK 1,300 if handing in a paper. The fee covers the course, coffee/tea, lunch and one dinner.

Minimum number of participants
16

Maximum number of participants
18

Location
Copenhagen Business School
Solbjerg Plads 3
2000 Frederiksberg
Room: SP108 (1st floor)

Contact information
The PhD Support
Katja Høeg Tingleff
Tel.: +45 38 15 28 39
E-mail: kht.research@cbs.dk

Registration deadline
25/03/2019

Please note that your registration is binding after the registration deadline.

In case we receive more registrations for the course than we have places, the registrations will be prioritized in the the following order: Students from Doctoral School of Organisation and Management Studies (OMS), students from other CBS PhD schools, students from other institutions than CBS.
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