DRE 1011 Quantitative Research Methods: Multivariate Statistics

DRE 1011 Quantitative Research Methods: Multivariate Statistics

Course code: 
DRE 1011
Department: 
Economics
Credits: 
6
Program of study: 
Doktorgradsstudium
Course coordinator: 
Ulf Henning Olsson
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2020 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

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Learning outcomes - Knowledge

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.
 

Learning outcomes - Skills

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".

General Competence

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Course content

Module 1

  • Regression analysis (OLS and 2SLS)
  • Logistic Regression/Probit Regression
  • ​Analysis of Variance

Module 2

  • Censored Regression
  • ​Multivariate Regression
  • EFA (Exploratory factor analysis)

Module 3

  • CFA (Confirmatory factor analysis)
  • SEM (Structural Equation Modeling)
  • Multigroup Analysis
  • ​Analysis of Logitudinal Data
Teaching and learning activities

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Software tools
Lisrel
R
SPSS
Stata
Additional information

In addition, the software tools STAT and MPlus will be used.

Qualifications

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

Required prerequisite knowledge

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Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
DRE 10111
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
100No2 Month(s)Individual The paper should be original work, and be written specifically for this course.
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:No
Grouping (size):Individual
Duration:2 Month(s)
Comment:The paper should be original work, and be written specifically for this course.
Exam code:DRE 10111
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Group work / Assignments
80 Hour(s)
Specified learning activities (including reading).
Student's own work with learning resources
50 Hour(s)
Autonomous student learning (including exam preparation).
Teaching on Campus
30 Hour(s)
Sum workload: 
160

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.