# Teaching

• STAT 647: Advanced Multivariate Analysis, Spring 2021 (ISU).
Theoretical course introducing both classical and high dimensional multivariate methods and their theories. The contents include multivariate random vectors and its distribution, dependence measures and copula, Wishart distribution, concentration Inequality, random matrix theory, Hotellingâ€™s test, high-dimensional inference for mean and covariance, signal detection and identification.

• STAT 475 / 575: Introduction to Multivariate Data Analysis, Fall 2020, Fall 2021 (ISU).
Statistical and graphical methods for analyzing multivariate data; organizing and summarizing analyses of multivariate data; principal components and factor analysis; classification; clustering; R statistical software package and the use of Rstudio to create reports (RMarkdown and GGplot).

• STAT 347: Probability and Statistical Theory for Data Science, Fall 2019 (ISU).
Topics include introduction to probability, random variables and distribution functions; sampling distributions; theory of estimation; theory of inference; use of R statistical package for simulation and data analysis.

• STAT 501: Multivariate Statistical Methods, Spring 2019, Spring 2020 (ISU).
Topics include multivariate normal distribution; simultaneous analysis of multiple responses; MANOVA; high dimensional regression; PCA; factor analysis; classification methods.

• DS 202: Data Acquisition and Data Exploratory Analysis, Fall 2018 (ISU).
Topics include Data acquisition, web-scraping, types of data displays, numerical and visual summaries of data, strategies and techniques for data visualizations, pipelines for data analysis.

• STAT 980: Advanced Probability Theory, Fall 2017 (UNL).
Topics include measure theory, Lebesgue-Stieltjes integration, Radon-Nikodym derivative, product space, conditional probability, law of large numbers, central limit theorems.

• STAT 892: Modern Nonparametric Statistics, Spring 2017 (UNL).
Develop a new graduate elective course curriculum on modern nonparametric statistics, which covers kernel smoothing estimator for probability densities, Nadaraya-Watson estimator, local polynomial regression, bootstrap and goodness-of-fit test.

• STAT 892: TA Training, Fall 2015, Fall 2016, Fall 2017 (UNL).
Train graduate TAs to be independent course instructors for intro-level statistical courses, Stat 218 and Stat 380. This course aims to help those TAs prepare their teaching portfolios, write quizzes and exams with detail rubric and develop in-class activities.

• STAT 380: Statistics and Applications, Spring, Fall 2016, Spring 2018 (big session class, UNL).
The first calculus-based statistic course for undergraduate students. Topics include probability, random variable, probability distribution and expectation, t, F and chi-square sampling distributions, estimation and confidence interval, hypothesis testing, and regression analysis with applications.

• STAT 218: Introduction to Statistics, Fall 2015, Fall 2016 (big session class, UNL).
The first statistic course for undergraduate students. The goal of this course is to teach students the practical application of statistical thinking to contemporary issues, collection and organization of data and statistical inference for decision making.

• STAT 462 and 463: Mathematical Statistics I and II, Fall 2014 and Spring 2015 (UNL).
Required statistics course for undergraduate actuarial science students. Stat 462 covers probability theories, special distributions and sampling distributions, and Stat 463 is about statistical inference including point estimation (sufficiency and completeness), interval estimation, uniformly most powerful tests, likelihood ratio test, ANOVA and regression analysis.

• STAT 305: Engineering Statistics, Spring 2014, Fall 2013 and Spring 2013 (ISU).
Introduction of Statistics to undergraduate engineering students. This course covers basic knowledge of data collecting, presenting and elementary statistical inference.