Zsolt Pajor-Gyulai, Courant Instructor

2018 Spring - Mathematical Statistics (MATH-UA.0234)

  • This course is an introduction to the mathematical foundations and techniques of modern statistical analysis, the fundamental tool for the interpretation of data in quantitative sciences. The course page is maintained on GitHub, while homework assignment and submission will be done through NYUClasses.

  • Statistical literacy is essential for anybody who wishes to understand and work with data. The steadily growing demand for skilled data scientist in both industry and academia attracts more and more people to this field. Being well versed in the mathematical foundations is certainly a way to stick out in the competitive job market. While this is not a machine learning course (although, if time permits, we will cover a few simple classification methods), it will provide solid foundations for anyone who wishes to continue in that direction.
  • As this is a math class, the main focus will be on the theory underlying statistical concepts. Be advised that we will not simply learn recipes. You will be expected to understand the theory and to be able to write your own logical explanations or proofs. Succesful completion of Theory of Probability or an equivalent course is assumed and the probability material will only be briefly reviewed.
  • Since this is a course about data, you will work with actual examples using Python Pandas with Jupyter Notebooks. While previous familiarity with Python is not expected, it will certainly be helpful. We will provide references to tutorials combined with plenty of sample notebooks and you will be expected to pick things up on the fly using these aids. We recommend that you start preparing ahead of time, check back later for references.

Previous Teaching

New York University

  • MATH-UA.0325 Analysis (Fall 2017)
  • MATH-GA.2901 Basic Probability (Spring 2017)
  • MATH-UA.0120 Discrete Mathematics (Fall 2016)
  • MATH-UA.0120 Discrete Mathematics (Spring 2016)
  • MATH-UA.0121 Calculus I (Fall 2015)

University of Maryland

  • MATH240: Linear Algebra (Spring 2014)
  • MATH246: Ordinary Differential Equations with Matlab (Summer 2013)
  • MATH246: Ordinary Differential Equations (Fall 2012)

Budapest University of Technology and Economics (Pre-2010)

  • Introduction to Calculus for Architects
  • Introduction to Calculus for Engineers
  • Introduction to Probability for Physicists