APPLIES TO ACADEMIC YEAR 2012/2013
DRE 1011 Quantitative Research Methods: Multivariate Statistics|
Responsible for the course
Department of Economics
According to study plan
Language of instruction
The aim of the course is to give the students training in areas of advanced multivariate statistics, by teaching them some of the most popular computer based methods applied in social science statistics. The course will also focus on basic statistical theory as well as on critical use of statistics in research. There will also be discussions and presentations of some of the latest research within parametric methods and non-normality.
After undertaking this course the student should be able to apply several multivariate statistical techniques, use modern statistical software and apply these on their research projects. They should also have acquired enough basic knowledge so that they on their own can extend their statistical “tool box.”
Admission to a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of admission to a PhD programme when signing up for a course with the doctoral administration. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on courses does not permit registration for courses, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses
Bartholomew, David and Steele, Fiona et al. 2008. Analysis of Multivariate Social Science Data. Second Edition. Chapman and Hall/CRC
Raykov, T & Marcoulides, G.A. A first course in Structural Equation Modeling. 2nd. edition. Psychological press
Collection of articles:
A collection of articles
The following methods will be covered
Regression analysis (OLS and 2SLS)
Analysis of Variance
EFA (Exploratory factor analysis)
CFA (Confirmatory factor analysis)
SEM (Structural Equation Modeling)
Software: SPSS and LISREL 8.80
Learning process and workload
Workload (6 ECTS)
Lectures 30 hours
Specified learning activities (including reading) 80 hours
Autonomous student learning (including exam preparation) 50 hours
Total 160 hours
Individual term paper will account for 100% of the grade. The paper should be original work, and be written specifically for this course.
Term paper will use the ECTS grading scale, A- F
DRE 10111 counts for 100% of the final grade.
Examination support materials
Next time the course is offered
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed.
Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honor code and academic integrity. If you have any questions about your responsibilities under the honour code, please ask.
© Copyright BI Norwegian Business School