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Advanced Quantitative Research Methods



GED:Methods, ID:Methods, PS:Methodsc, EES:Methods, S:Methods, GPH:Methods

Admissions requirements

Statistics, Mathematics, and Quantitative Research Methods.


The course introduces students to selected topics in advanced quantitative research with application in economics, political science, environmental science and other. The aim of the course is to help students understand more advanced statistical methods in the context of applied quantitative research practice. The course builds on students’ understanding of basic inferential theory and linear regression and familiarizes them with new statistical techniques, including time series and panel models, choice models, and other. Students will be asked to develop a project of their choosing in their area of interest that incorporates some of these statistical techniques.

Course objectives

  • Provide basic understanding of more advanced statistical techniques.

  • Match a statistical method to a research question and an argument.

  • Understand how these techniques can be applied in the context of substantive research topics.

  • Further develop statistical programming skills in R package, including graphical display of data.

  • Present quantitative findings to varied types of audiences.


Once available, timetables will be published here.

Mode of instruction

The course consists of Interactive lectures, where students are required to participate and demonstrate their familiarity with readings and lab seminars dedicated to improving the conceptual understanding of these methods in a series of mini research projects conducted in R.


In-class participation consists of completed lab seminar reports each week. The final research project will also require a submission of a number of research updates throughout the course that will count towards the final grade.

Participation, 15%, Ongoing Weeks 1-7
Project presentation, 15%, Weeks 6 and 7
Project Update, 10%, Week 2
Method notes, 5 %, Week 3
Final Research Project, 30%, Week 8
Exam, 15%, Week 4
Group project, 10%, Week 5 and 6


There will be a Blackboard site available for this course. Students will be enrolled at least one week before the start of classes.

Reading list

Required Textbook:
Dougherty, Christopher. 2007. Introduction to Econometrics – Fourth Edition. Cambridge University Press.

Gujarati, Damodar. 2008. Basic Econometrics. McGraw-Hill/Irwin; 5 edition.
Kennedy, Peter. 2008. A Guide to Econometrics. Wiley-Blackwell; 6 edition
Michael J. Crawley. 2005. Statistics: An Introduction using R, 1st Edition. Wiley-Blackwell, Paperback.
The Chicago Guide to Writing About Numbers (2004), Haack, Dennis, University of Chicago Press – 1st edition.


This course is open to LUC students and LUC exchange students. Registration is coordinated by the Curriculum Coordinator. Interested non-LUC students should contact



OPTIONAL PREPARATION BEFORE FIRST SESSION: Review of Basics in Linear Regression: Dougherty: Simple Regression Analysis (Chapter 1); Properties of the Regression Coefficients and Hypothesis Testing (Chapters 2), Multiple Regression Analysis (Chapter 3)