Current & Recent Teaching

Fall 2018
  • Math 541B - Mathematical Statistics
    Second semester of the core graduate mathematical statistics sequence. Topics: Hypothesis tests and their optimality theory, the Neyman-Pearson lemma, generalized likelihood ratios, confidence regions, asymptotic theory, jackknife & bootstrap methods, the EM algorithm, and Monte Carlo simulation methods including Markov chain Monte Carlo.
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  • Math 595 - Practicum in Teaching the Liberal Arts: Mathematics
    Practical principles for the long-term development of effective teaching within college disciplines.
    Blackboard

Spring 2017
  • Math 542L - Analysis of Variance & Regression
    A graduate-level introduction to regression and ANOVA models with statistical computing laboratory. Topics: Basics of multivariate statistics, ordinary and generalized least squares estimation in the linear model, the F-test, multiple comparisons and confidence intervals, equivariance and invariance, ridge regression and the lasso, analysis of variance, random effects models, and applications with statistical computing.
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  • Math 500 - Graduate Colloquium

Fall 2016
  • Math 307 - Statistical Inference and Data Analysis I
    Math 307 (and its companion course, Math 308) provide instruction in both the mathematical basis for modern statistical techniques as well as their latest and most important applications. These classes are also the core of the Statistics Minor offered by the Mathematics Department. Topics: Probability, counting, independence, distributions, random variables, simulation, expectation, variance, covariance, transformations, law of large numbers, Central limit theorem, estimation, efficiency, maximum likelihood, Cramer-Rao bound, the bootstrap. Also, statistical computing using the software package R is featured prominently throughout the course.
    Blackboard

  • Math 595 - Practicum in Teaching the Liberal Arts: Mathematics
    Practical principles for the long-term development of effective teaching within college disciplines.
    Blackboard

Spring 2016
  • Math 308 - Statistical Inference and Data Analysis II
    Math 308 (and its companion course, Math 307) provide instruction in both the mathematical basis for modern statistical techniques as well as their latest and most important applications. These classes are also the core of the Statistics Minor offered by the Mathematics Department. Topics: Confidence intervals, hypothesis testing, p-values, likelihood ratio, nonparametrics, descriptive statistics, regression, multiple linear regression, experimental design, analysis of variance, categorical data, chi-squared tests, Bayesian statistics. Also, statistical computing using the software package R is featured prominently throughout the course.
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  • Math 500 - Graduate Colloquium

Fall 2015
  • Math 307 - Statistical Inference and Data Analysis I
  • Math 595 - Practicum in Teaching the Liberal Arts: Mathematics

Spring 2015
  • Math 542L - Analysis of Variance & Regression

  • Math 545L - Introduction to Time Series
    A graduate-level introduction to the theory and methods of the analysis of time series data. Topics: Stationary and nonstationary stochastic processes, trend removal, the multivariate normal distribution, Hilbert spaces and the projection theorem, linear regression, autoregressive moving average (ARMA) models, estimation of mean and autocorrelation functions via maximum likelihood and least squares, and applications with statistical computing in R.
    Blackboard



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