Statistical Inference

Course Description

The aim of the course is to give an introduction to the basic concepts of statistics that are pre-requisites for big data analysis and machine learning. We will start with basic notions of probability theory, then discuss parameter estimations and hypothesis testing and, finally, learn several regression models.

Course tools

R

Prerequisits

Basic math, basics of the probability theory

Lecturer

Rostyslav Hryniv

Dr. Rostyslav Hryniv
Professor at the Ukrainian Catholic University, head of Applied Mathematics department

Awards, grants and fellowships:

  • 2007: Grant DMS-0710477, National Science Foundation, U.S.A.
  • 2005/07: Grant 436 UKR 113/84 (Co-Principal investigator in Ukraine) from Deutsche Forschungsgemeinschaft, Germany
  • 2004/06: Alexander hom Humboldt Fellowship, the University of Bonn, Germany
  • 2003: Prize of the President of Ukraine for Young Scientists
  • 1998/99: PIMS Postdoctoral Fellowship and the University of Calgary, Canada
  • 1994/95: Soros Graduate Student

Teaching experience:

  • 2011/16 – Lecturer in Mathematics and Financial Mathematics at the Kyiv School of Economics
  • 2009 – Lecturer in Financial Mathematics, Stochastic Analysis, Applied Statistics at the University of Rzeszów, Poland
  • 2009 – Mini-course (6 lectures) “An introduction to the Black–Scholes model” at the Kyiv Mohyla Business School (KMBS), Kyiv, Ukraine
  • 2007 – Mini-course (4 lectures) “Inverse spectral problems for singular Sturm–Liouville operators” at the University of Kentucky, Lexington, KY, U.S.A.
  • 2000 – Lecturer in Mathematical and Applied Statistics and Financial Mathematics at the Lviv Franko National University, Ukraine
  • 1998 – Lecturer in Analysis at the University of Calgary, Canada

Fields of interests: Analysis and Probability and their applications to Inverse Problems, Image Recognition, Financial Mathematics.

Contacts: [email protected]