About
Hi and welcome to my site!
Since 2002, I have been at Pomona College where I teach lots of different kinds of statistics, taught a little bit of math once, love teaching writing with statistics, and hope to soon teach some data science.
Background
My undergraduate degree in Mathematics is also from Pomona College, where I worked with Don Bentley. I did my PhD in Statistics at UC Davis with David Rocke. I was interviewed (August 2020) for Pomona College's Sagecast where you can hear me talk about my path.Here to learn?
Me too! So many good things to learn. I've posted all of my course materials freely, and I hope they give you inspiration either as a teacher or a student. I've also written an OpenIntro textbook with the fantastic Mine Çentinkaya-Rundel. Introduction to Modern Statistics focuses on computational inference and multivariable modeling & visualizing, and it is available for free online.Interested in my research?
One of the best things about being a statistician is the many different subject areas to pursue. My research projects are posted, but if you have time, it's really my students' research projects that are worth investigating. I highly recommend working with undergraduates on research as it is among the most fun and rewarding parts of my day.My areas of expertise include statistical analysis of high-throughput genetic data which don’t conform to technical conditions in standard methods. I work on problems of normalizing data structures, clustering and classifying time course profiles, and creating metrics to measure a variety of signals.
I chose to become a statistician because of the myriad potential collaborations across many fields. I have worked with medical doctors, biologists, geologists, and physicists in my research. Through new ventures into data science (both research and teaching), I am currently exploring ways that today’s extensive data (both in scale and in occurrence) are shaping science and the world around us.
Want to know what I'm up to?
Beyond teaching and research, I am fortunate to be able to fit in a few hours here and there on some of my passion projects. Almost every Tuesday, I wrangle a bit of TidyTuesday data. I'm also compiling a list of scholars who are traditionally underrepresented in the statistics and data science curriculum. Feel free to use the list for your own "scholar of the day" classroom activity. And please submit a pull request or a GitHub issue if you have names to add to the database!blog
Dear Data - Solitude
Contribution to “Solitude”, a project to display part of the permanent collection of the Benton Art Museum at Pomona College.
Read moreTeaching with The Islands
One of my favorite class activities involves the virtual world known as The Islands. Students, too, love the project.
Read moreRelative Risk and Odds Ratios
Why relative risk should not be calculated on data sampled using a case control study.
Read moreCourses
Math 150: Methods in Biostatistics
Methods in Biostatistics is a second course in statistics focused on topics and data found in the life sciences. No biology background is needed, but interest in the life sciences is important.
Read moreMath 58B: Introduction to Biostatistics
Introduction to Biostatistics is a first course in statistics focused on topics and data found in the life sciences. No biological background is needed, but interest in the life sciences is important.
Read moreData Sources
A compilation of many different types of data sources.
Read moreMath 151: Probability Theory
Math 151 is an introduction to probability for students with a calculus background and no prerequisites of probability or statistics. Though the course will be focused on the theoretical aspects of the material, there will be some real world applications in class and in the homework assignments. The idea is to have a strong mathematical understanding of the concepts while also understanding how the concepts are applied in the real world.
Read moreadventures outside the classroom
IMS
Introduction to Modern Statistics puts a heavy emphasis on exploratory data analysis (specifically exploring multivariate relationships using visualization, summarization, and descriptive models) and provides a thorough discussion of simulation-based inference using randomization and bootstrapping, followed by a presentation of the related Central Limit Theorem based approaches.
Read moreResearch projects
Papers + Projects
A collection of research papers, many of which were done primarily by undergraduate collaborators.
Read more