## Winter 2022

##### This is a list of potential topics for Winter 2022 that will be listed on the application, but the actual set of topics that will be offered is subject to change.

* If a mentor is listed for multiple project topics, they will choose which project to offer based on the interest of applicants. If you are really interested in a statistical topic that is not listed for this quarter, feel free to let us know on the application- a few mentors are willing to switch their topic if a student has strong interests. *

#### Medha Agarwal: Statistical Simulations

*Prerequisites:*STAT 311, programming experience (preferably in R/Python)

#### Michael Cunetta: Sabermetrics

*Prerequisites:*Familiarity with the rules of major league baseball. Some familiarity with R.

#### Nina Galanter: Optimal Treatment Rules: Causal Inference and Statistical Learning

*Prerequisites:*Some familiarity with conditional probability, linear regression, and R.

#### Jess Kunke: Survey statistics

*Prerequisites:*The project can be tailored based on the student's background knowledge; some prior exposure to concepts such as mean, variance, and probability would be helpful.

#### Jess Kunke: Simulating data

*Prerequisites:*The project can be tailored based on the student's background knowledge; some prior exposure to concepts such as mean, variance, and probability would be helpful.

#### Nick Irons: Bayesian Data Analysis

*Prerequisites:*Knowledge of probability at the level of STAT 311 and some familiarity with programming.

#### Erin Lipman: Bayesian perspectives on statistical modeling

*Prerequisites:*Some familiarity with multivariate linear regression will be helpful, as will some familiarity with R. Our project can be either more technical or more conceptual depending on the background and interests of the student.

#### Anna Neufeld: Multiple Testing

*Prerequisites:*Stat 311 and some knowledge of R will be helpful, but not required.

#### Anna Neufeld: Introduction to Clinical Trials

*Prerequisites:*None.

#### Sarah Teichman: Multivariate Data Analysis

*Prerequisites:*Stat 311, and linear algebra would be helpful but not necessary

#### Seth Temple: Statistical Genetics I: Pedigrees and Relatedness

*Prerequisites:*STAT 311, and some programming experience

#### Seth Temple: Statistical Genetics II: Genome-wide Association Studies

*Prerequisites:*STAT 340/1/2, or a course in linear modeling (regression analysis)

#### Seth Temple: Statistical Genetics III: Markov Models

*Prerequisites:*STAT 394/395, or a math course in stochastic processes

#### Drew Wise: Introduction to Nonparametric Statistics

*Prerequisites:*An introductory statistics class is all that's needed. Some programming experience would be a plus.