DRE 7008 Advanced Statistics

DRE 7008 Advanced Statistics

Course code: 
DRE 7008
Department: 
Economics
Credits: 
6
Course coordinator: 
Genaro Sucarrat
Course name in Norwegian: 
Advanced Statistics
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2022 Autumn
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

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.

Learning outcomes - Knowledge

After taking this course, students should have a solid knowledge of the foundations of statistical applications.

Learning outcomes - Skills

After taking this course, students should be able to use statistical methods for research-related purposes, and advanced programming in data analysis.

General Competence

After taking this course, students should be able to critically reflect on and evaluate others’ use of statistical methods for research-related purposes.

Course content

1. Probability and Random Variables

2. Expectation and Conditional Expectation

3. Estimation and Inference

4. Computation and Numerical Optimisation

5. Model Selection

Teaching and learning activities

The course will we taught in modules, each consisting of three hours. Students are expected to participate in class and solve exercises.

Software tools
R
Additional information

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Qualifications

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 courseleader. 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.

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

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Assessments
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
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
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)
Sum workload: 
180

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.