Teaching

2019-2020 academic year:

  • Math 315: Bayesian statistics (Fall)
  • Math 280: Statistical consulting (Fall, Winter, Spring)
  • Math 285: Introduction to data science (Spring)

Past courses:

  • Math 215: Introduction to statistics
  • Math 245: Applied regression
  • Math 265: Probability
  • Math 275: Introduction to statistical inference

Recent Publications

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Recent Talks

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Projects

Data Science for Statistics

Tutorials and case studies teaching data-scientific concepts in statistics courses.

lmeresampler: Bootstrapping Clustered Data in R

Providing an easy way to bootstrap nested linear-mixed effects models using either the parametric, residual, cases, CGR (semi-parametric), or random effects block (REB) bootstrap fit using either lme4 or nlme.

qqplotr: ggplot2 Compatible Quantile-Quantile plots in R

Extending ggplot2 to provide a complete implementation of Q-Q plots.

Recent Posts

In June I attended an ACM workshop focused on how the ACM can facilitate sharing elements of a data science curriculum across institutions. This is my recap.

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The analyses that get me excited are not Google crunching a terabyte of web ad data in order to optimize revenue… [but rather] the biologists who are absolutely passionate about this one swampfly and now they can use R and they can understand it.

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The Upshot takes a look at who’s in and who’s out of the first Republican debate taking into account sampling variability.

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