David Dalpiaz
Data ImporterExporter
Hello and welcome to my webzone! I am currently a Teaching Assistant Professor for the Department of Statistics at the University of Illinois UrbanaChampaign.
After a BS in Mathematics @ Illinois, I completed a PhD in Statistics, also at Illinois, under the supervision of Ping Ma. I then spent four years as a Visiting Assistant Professor, then Lecturer and MS Academic Advisor for Statistics @ Illinois.
I previously spent a year as an Associated Assistant Professor and Data Analytics Program Specialist for the Department of Statistics at The Ohio State University. While away from Illinois, I was an Adjunct Teaching Assistant Professor for Statistics @ Illinois where my course Statistical Modeling in R is part of the online Master of Computer Science in Data Science.
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

20220402 /// Recreating NFL Scorigami with R

20200817 /// Ten Simple Rules for Success in STAT 432

20191127 /// Letters of Recommendation

20190822 /// The Extended Syllabus
Teaching
University of Illinois UrbanaChampaign
 STAT 100: Statistics
 STAT 200: Statistical Analysis
 STAT 212: Biostatistics
 STAT 385: Statistical Programming Methods
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 STAT 400: Statistics and Probability I
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fa17
 STAT 420: Statistical Modeling in R
su17
 Taught as part of the Master of Computer Science in Data Science program in collaboration with Coursera. I currently maintain an opensource textbook, Applied Statistics with R for use with the course.
 STAT 432: Basics of Statistical Learning
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fa20
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 Covers the entirety of An Introduction to Statistical Learning with Applications in R. I currently maintain an opensource supplemental textbook, R for Statistical Learning which focuses on using R to perform statistical learning techniques.
 STAT 510: Mathematical Statistics
sp22
sp21
fa20
 STAT 593: STAT Internship
Ohio State University
Textbooks
 Applied Statistics with R
 Currently in use for STAT 420 both inperson 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 rewrite. 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.