David Dalpiaz
Data Importer-Exporter
Hello and welcome to my webzone! I am currently a Teaching Assistant Professor for the Department of Statistics at the University of Illinois Urbana-Champaign.
What am I working on?
- Teaching STAT 385, a statistical programming course.
- Writing Atomic R, a textbook introducing the R programming language.
- Developing
bbd, an R package for accessing baseball data. - Contributing to the PrairieLearn R autograder.
- Researching accessibility needs and best practices in STEM education.
- Applying statistical methodology to public baseball data.
Contact
The best way to reach me is by email. I have a work phone, but I honestly don’t know the number and I respond faster to email anyway.
- Email: dalpiaz2@illinois.edu
- Office: Who knows?
- GitHub: daviddalpiaz
Blog
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2023-03-30 Moneyball in R
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2023-02-09 Reduce Friction, Increase Learning
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2022-10-04 Accessing Baseball Data for Analysis with R
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2022-04-02 Recreating NFL Scorigami with R
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2020-08-17 Ten Simple Rules for Success in STAT 432
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2019-11-27 Letters of Recommendation
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2019-08-22 The Extended Syllabus
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Teaching
University of Illinois Urbana-Champaign
- STAT 100 Statistics
- STAT 200 Statistical Analysis
- STAT 212 Biostatistics
- STAT 385 Statistical Programming Methods
sp23fa22sp22fa21 - STAT 400 Statistics and Probability I
sp18fa17 - STAT 420 Statistical Modeling in R
su17 - STAT 432 Basics of Statistical Learning
sp21fa20sp20fa19sp18fa17 - STAT 510 Mathematical Statistics
sp22sp21fa20 - STAT 593 STAT Internship
Ohio State University
Textbooks
- Applied Statistics with R
- Currently in use for STAT 420 both in-person and online at Illinois for the Departments of Statistics and Computer Science.
- R for Statistical Learning / Basics of Statistical Learning
- Perpetually undergoing considerable changes and developments, including an attempt at a complete re-write. Originally intended to be supplemental notes to ISL in order to provide additional examples in R, the text is starting to become a complete reference text for STAT 432, Basics of Statistical Learning, at Illinois for the Department of Statistics. Target audience is advanced undergraduate students in statistics with previous experience with R and regression.