954406

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 Business and Politics, CBS

Associate Professor Charles T. Tackney and Assistant Professor Jan Michael Bauer, both from the Department of Management, Society and Communication, CBS

Course Coordinator

Associate Professor Manuel Citi

Prerequisites

Participants must be enrolled as PhD students in an institution of tertiary education.

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.

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).

Aim

We first assess the perceived quantitative methods skills and needs of doctoral students that participate in the course through a pre-course survey. In the course, we introduce and train students in the targeted statistical tools within a pedagogic context of a general empirical method that recognizes the complementarity between qualitative and quantitative methods. This should significantly help prepare students for the particular challenges they immediately face as well as any future methods issue that may arise in the course of a post-doctoral career that involves organizational and management research.

Course content

1. An Introduction to General Empirical Method:
History, Culture, and Science and the Role of Critical Realism for Research Insight - Classical and Statistical Heuristic Structures- Complementarity Among and Between Insight, Heuristic Structures, and the Research Field

2. Statistical Procedures of Interest (Content will vary to a degree, depending on pre-course student survey data)
a) A Session of Review and/or Remediation: Statistics as description, Statistics for inference, how these differ: the normal distribution and the Central Limit Theorem
b) Introduction of Stata (enter data, clean data, writing procedures, data preparation)
c) Estimation and explanation of statistical models (t-tests, ANOVA, correlation analysis, regression analyses as indicated and to the depth needed)
d) Interpretation of results
e) Class discussions and/or individual sessions on the application of quantitative methods to individual research questions

Teaching style

Lecture and discussion sessions will be alternated with PC lab and/or group work. C. Tackney will provide the initial lecture on General Empirical Method. M. Citi and J. Bauer, will work together to present specific statistics sessions, hands on exercises and group work. The intended course runs (three) five days, combining morning and afternoon sessions.

Lecture plan

Preliminary lecture plan

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

Time/period	Faculty	Title	Readings
28 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, JMB	Session 2: Introduction to data handling and Stata + hands on (data cleaning and preparation)	M&J (2017) Ch: 1; 2.1-2.3
15.45 - 17.00	MC	Session 3: Descriptive statistics and graphs	M&J (2017) Ch: 2.4
29 May
09.00 - 10.30	MC, CT	Session 4: A Session of Review and/or Remediation
10.45 - 12.15	MC	Session 5: Estimation and interpretation of descriptive statistics – hands on
13.15-15.00	MC	Session 6: Explanation of testing differences (e.g., t-tests, ANOVA)	M&J (2017) Ch: 2.5
15.30 - 17.30	MC	Session 7: Estimation and interpretation of testing differences (e.g., t-tests, ANOVA) – hands on
30 May
09.00 – 10.30	JMB	Session 8: Explanation, estimation and interpretation of bivariate relationships: scatterplots and correlation analyses	A (2008)
10.45 – 12.15	JMB	Session 9: Explanation of regression analyses - OLS basics & bivariate	M&J (2017) Ch: 3
13.15 – 15.00	JMB	Session 10: Explanation of regression analyses - OLS multivariate & moderation effects	M&J (2017) Ch: 4, 5, 6
15.30 - 17.00	JMB	Session 11: Estimation and interpretation of regression analyses - hands on
2 days add-on
31 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, MC, JMB	Session 13: Class discussion and/or individual sessions on the application of quantitative methods to individual research questions
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	Session 15 Groups exercise 1: Apply methods to answer a specific research questions
1 June
09.00 - 10.30	MC, JMB	Session 16: Groups exercise 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, MC, JMB	Session 18: Class discussions on the application of quantitative methods to individual research questions and debriefing and 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 quantitative 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

28/05/2018

End date

01/06/2018

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.Other readings as suggested by the doctoral student skills and interests assessment survey.Recommended literatureGreene, 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 ServicesBaum, C. (2006). An introduction to modern econometrics using Stata. College Station, TX: Stata Press.

Fee

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

Minimum number of participants

Maximum number of participants

Location

Copenhagen Business School
Solbjerg Plads 3
2000 Frederiksberg
Room: SP108

Contact information

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

Registration deadline

17/04/2018

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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