878445

Course

Applied Quantitative Methods for Non-quantitative Doctoral Researchers in Organization and Management Studies (runs annually)

Faculty

Associate Professor Wencke Gwozdz, Associate Professor Charles T. Tackney, and Assistant Professor Jan Bauer (ICM), all from the Department of Intercultural Communication and Management, CBS

Course Coordinator

Associate Professor Wencke Gwozdz

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.

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.

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 hand in a paper or not.

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, factor analysis, 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

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 he, W. Gwozdz and J. Bauer will work together to present specific statistics sessions in the afternoon. The intended course runs five days, combining morning and afternoon sessions.

Lecture plan

Time/period	Faculty	Title
29 May	Charles T. Tackney	Session 1: An Overview of the Place of Quantitative Studies in General Empirical Method
Wencke Gwozdz	Session 2: Introduction to data handling and Stata + hands on (data cleaning and preparation)
Wencke Gwozdz	Session 3: Explanation of descriptive statistics
30 May	Wencke Gwozdz with Charles T. Tackney	Session 4: A Session of Review and/or Remediation
Wencke Gwozdz	Session 5: Estimation and interpretation of descriptive statistics – hands on
Wencke Gwozdz	Session 6: Explanation of testing differences (e.g., t-tests, ANOVA)
Wencke Gwozdz	Session 7: Estimation and interpretation of testing differences (e.g., t-tests, ANOVA) – hands on
Dinner
31 May	Wencke Gwozdz	Session 8: Explanation of testing relationships (correlation analyses)
Charles T. Tackney/ Wencke Gwozdz	Session 9: Class discussion and/or individual sessions on the application of quantitative methods to individual research questions
Wencke Gwozdz	Session 10: Estimation and interpretation of testing relationships (correlation analyses) – hands on
Wencke Gwozdz	Session 11: Explanation of regression analyses - OLS
1 June	Wencke Gwozdz	Session 12: Estimation and interpretation of regression analyses – OLS – hands on
Charles T. Tackney/ Wencke Gwozdz/ Jan Bauer	Session 13: Class discussion and/or individual sessions on the application of quantitative methods to individual research questions
Jan Bauer	Session 14: Explanation, estimation and interpretation of OLS assumptions – hands on
Jan Bauer	Session 15 Explanation, estimation and interpretation of regression analyses Logit – hands on
2 June	Jan Bauer	Session 16: Explanation, estimation and interpretation of factor analysis
Jan Bauer	Session 17: Outlook – more advanced regression models (e.g., longitudinal regression analysis, multilevel analyses)
Charles T. Tackney/ Wencke Gwozdz/ Jan Bauer	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 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

N/A

Start date

29/05/2017

End date

02/06/2017

Level

PhD

ECTS

5 (Including Add-on: + 1 ECTS). When registering, please decide whether to hand in a paper or not, see the Prerequisites above

Language

English

Course Literature

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.Other readings as suggested by the doctoral student skills and interests assessment survey.Recommended literature:Greene, W.H. (2011). Econometric Analysis, 7th edition, Prentice Hall.Howell, D.C. (2010). Statistical Methods for Psychology. Wadsworth, CA: Cengage Learning.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 6,500 - or DKK 7,800 if you submit paper. Covers the course, coffee/tea, lunch and one dinner

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

25/04/2017

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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