DRE 1011 Quantitative Research Methods: Multivariate Statistics
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".
- Regression analysis (OLS and 2SLS)
- Logistic Regression/Probit Regression
- Analysis of Variance
- Censored Regression
- Multivariate Regression
- EFA (Exploratory factor analysis)
- CFA (Confirmatory factor analysis)
- SEM (Structural Equation Modeling)
- Multigroup Analysis
- Analysis of Logitudinal Data
In addition, the software tools STAT and MPlus will be used.
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
|Exam category||Weight||Invigilation||Duration||Grouping||Comment exam|
Form of assessment:
Internal and external examiner
Examination when next scheduled course
|100||No||2 Month(s)||Individual||The paper should be original work, and be written specifically for this course.|
|Form of assessment:||Written submission|
|Comment:||The paper should be original work, and be written specifically for this course.|
|Exam code:||DRE 10111|
|Resit:||Examination when next scheduled course|
Group work / Assignments
Student's own work with learning resources
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.