DRE 7008 Advanced Statistics
DRE 7008 Advanced Statistics
The aim of the course is to equip the students with a formal understanding of statistics at a level expected among PhD students in economics, finance and related disciplines.
After taking this course, students should have a solid knowledge of the foundations of statistical applications.
After taking this course, students should be able to use statistical methods for research-related purposes, and advanced programming in data analysis.
After taking this course, students should be able to critically reflect on and evaluate others’ use of statistical methods for research-related purposes.
1. Probability and Random Variables
2. Expectation and Conditional Expectation
3. Estimation and Inference
4. Computation and Numerical Optimisation
5. Model Selection
The course will we taught in modules, each consisting of three hours. Students are expected to participate in class and solve exercises.
-
Enrollment in 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 enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.
Covid-19
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
-
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Weight: 100 Grouping: Individual Duration: 1 Semester(s) Exam code: DRE 70081 Grading scale: Pass/fail Resit: Examination when next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Group work / Assignments | 75 Hour(s) | Specified learning activities (including reading). |
Student's own work with learning resources | 75 Hour(s) | Autonomous student learning (including exam preparation). |
Teaching | 30 Hour(s) |
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.