Office hours: Monday 10:00–12:00 and Friday 2–3:30.

Instructor: Prof. Eugene Demidenko

Prerequisites: Math 40 or by a special permission of the instructor.

Textbooks:

- Demidenko E (2020).
*Advanced Statistics with Applications in R*. Hoboken, NJ: Wiley: www.eugened.org - Hastie T, Tibshirani R, Friedman J (2009).
*The Elements of Statistical Learning*, 2d ed, Springer. Provided electronically on canvas.

Additional reading:

- D Zelterman,
*Applied Multivariate Statistics with R*, Springer, 2015. - WK HÃ¤rdle, L Simar,
*Applied Multivariate Statistical Analysis*, Springer, 2007. Provided electronically on canvas.

Course Objectives:

- Provide theoretical basis for
**multivariate**statistical analysis and optimal statistical hypothesis testing, point and interval estimation. - Learn about modern statistical methods of statistical analysis including nonlinear mod-
els,
**data mining**, and classification techniques. - Get experience in statistical solutions of
**real-life-high-volume**problems, including shape and image analysis, using statistical package R. - Preparation for a career in data analysis and
**statistical problem solutions**. - Programming in R is required.