Teaching
Books
Traditionally Published
Pruim, Randall. 2018. Foundations and Applications of Statistics: An Introduction Using R. 2nd ed. Vol. 28. Pure and Applied Undergraduate Texts. Providence, RI: American Mathematical Society. https://www.ams.org/publications/authors/books/postpub/amstext-28.
Wegener, Ingo. 2005. Complexity Theory: Exploring the Limits of Efficient Algorithms. Berlin: Springer-Verlag.
Schöning, Uwe, and Pruim, Randall. 1998. Gems of Theoretical Computer Science. Berlin: Springer-Verlag.
Online
Kaplan, Daniel, and Pruim, Randall. 2022. Statistical Modeling: A Fresh Approach.
Pruim, R. (2021). Statistics for the Physical Sciences and Engineering.
Horton, N. J., Pruim, R., & Kaplan, D. T. (2015, November). A student’s guide to R.
Pruim, R., Horton, N. J., & Kaplan, D. T. (2015, November). Start teaching with R.
Other Materials
Courses
I’ve taught a lot of different courses during my time at Calvin. Here’s a list. For some of the more recent ones you can click on the title of the course to get to a course website.
- CS 260 (Automata Theory)
- CS 360 (Complexity and Computability)
- Data 303 (Applied Modeling and Visualization) * Math 100 (Mathematics in the Contemporary World)
- Math 132 (Calculus for Management, Life, and Social Sciences)
- Math 156 (Discrete Mathematics for Computer Science)
- Math 171 (Calculus I)
- Math 172 (Calculus II)
- Math 221 (The Real Number System and Methods for Elementary School Teachers)
- Math 232 (Engineering Mathematics)
- Math 251 (Discrete Mathematics I)
- Math 252 (Discrete Mathematics II)
- Math 312 (Logic, Computability, and Complexity)
- Math 361 (Real Analysis)
- Math 362 (Real Analysis II)
- Math 381 (Mathematical Logic)
- MGMT 535 (Statistical Analysis)
- Stat 143 (Introduction to Probability and Statistics)
- Stat 145 (Biostatistics)
- Stat 241 (Engineering Statistics)
- Stat 243 (Statistics)
- Stat 341 (Computational Bayesian Statistics)
- Stat 343 (Probability and Statistics)
- Stat 343 (Mathematical Statistics)
- Stat W82 (Visualize This! with D3
I’ve also taught at some other places:
For The Institute for Statistics Education (statistics.com): Visualization in R with ggplot2
At University of Michigan: Biostatistics (for graduate students in public health)
At Boston University: Accelerated Intro Programming in C
At Providence College: Mathematics for the Liberal Arts