Students in the colloquium will discuss topics covered in the regular content of STOCKSCH 530 to gain more knowledge of the material. The will also discuss related topics to expand their knowledge of the subject of plant nutrition. They also will discuss subjects of the laboratory sections of the course and design an experiment that would enhance their experiential learning in the course.

Contact department for description.

Contact department for description.

The advanced theory of statistics, including methods of estimation (unbiasedness, equivariance, maximum likelihood, Bayesian, minimax), optimality properties of estimators, hypothesis testing, uniformly most powerful tests, unbiased tests, invariant tests, relationship between confidence regions and tests, large sample properties of tests and estimators. Prerequisites: Statistc 605 and 608.

Contact department for description.

Using data to estimate relationships between predictors and responses is an important task in statistics and data science. When datasets are large, modern methods have been developed that allow us to estimate those relationships without making strong assumptions about those relationships- i.e. we can let the data determine how E(y|x) relates to x. In statistics, these methods are generally referred to as ?nonparametric regression.? This applied graduate course will focus on learning to use nonparametric regression to analyze data. We will read a book, ?Semiparametric Regression with R,?

Distribution and inference for binomial and multinomial variables with contingency tables, generalized linear models, logistic regression for binary responses, logit models for multiple response categories, loglinear models, inference for matched-pairs and correlated clustered data.

This course provides an introduction to the statistical techniques that are most applicable to data science. Topics include regression, classification, resampling, linear model selection and regularization, tree-based methods, support vector machines and unsupervised learning. The course includes a computing component using statistical software.