Courses

• STAT 372: Introduction to Statistical Inference and Regression (Fall 02, Spring 03, Fall 03)
  Coverage: Statistical inference and regression analysis including theory and applications. Point and interval estimation of population parameters. Hypothesis testing including use of t, chi-square and F. Simple linear regression and correlation. Introduction to multiple regression and one-way analysis of variance.
  
  
  
• STAT 521: Statistical Inference I (Fall 06)
  Coverage: probability tools for statistics, including description of discrete and absolutely continuous distributions, expected values, moment generating functions, transformation of random variables, marginal and conditional distributions, independence, order statistics, multivariate distributions, concept of random sample, derivation of many sampling distributions.
  Please visit the course webpage for course description, syllabus, and homework assignments.
  
  
  
• STAT 522: Statistical Inference II (Spring 05, Spring 06, Spring 07)
  Coverage: general framework for statistical inference. Point estimators: biased and unbiased, minimum variance unbiased, least mean square error, maximum likelihood and least squares, asymptotic properties. Interval estimators and tests of hypotheses: confidence intervals, power functions, Neyman-Pearson lemma, likelihood ratio tests, unbiasedness, efficiency and sufficiency.
  Please visit the course webpage for course description, syllabus, and homework solutions.
  
  
  
• STAT 790C: Statistical Machine Learning and Data Mining (Fall 05, Fall 07)
  Coverage: statistical learning theories, modern data mining methodology, and their applications. Popular data mining tools such as penalized regression, support vector machines, classification and regression trees, neural network, boosting, kernel methods, dimension reduction and relevant software are introduced.
  Please visit the class webpage for course description, syllabus and homework solutions.
  
  
  
• STAT 790D: Introduction to Smoothing Methods and Nonparametric Regression (Fall 2003)
  An old version of STAT 790A.
  Visit class webpage for the course description.
  
  
  
• STAT 790A: Introduction to Smoothing Methods and Nonparametric Regression (Spring 07)
  This course gives an overview of classical and modern smoothing and nonparametric regression methodologies, with emphasis on both the theoretical and computational aspects. It also covers analysis of various types of real datasets including survival and longitudinal data. Special treatment is given to parameter tuning, model selection, and variable selection.
  Please visit the course webpage for course description, syllabus, and homework solutions.
  
  
  
• STAT 784: Multivariate Analysis

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