Course Overview

This graduate course in statistics concentrates primarily on basic statistical concepts such as random variables and distributions, estimation, testing, asymptotic approximations.

Learning Achievement

Qualification targets: Upon successful completion of the module "Advanced Statistics" students should have a sound theoretical background in statistics which is required in more applied and specialized quantitative courses. Imparted soft skills: Analytical thinking, Independent studying and learning, Critical thinking

Competence

Course prerequisites

Bachelor courses in Inferential Statistics and Basic Econometrics, background in Mathematical Analysis

Grading Philosophy

100 % Written exam (90 min)

Course schedule

Week1: Introduction Week2: followed by Week3 to the Final Week

Course type

Online Course Requirement

Instructor

Prof. Dr. Vasyl Golosnoy

Other information

a) Lecture b) Tutorial

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