David Dalpiaz
Data ImporterExporter
Hello and welcome to my webzone! You can call me Dave!
I am currently a Teaching Associate Professor for the Department of Computer Science at the University of Illinois UrbanaChampaign.
What am I working on?
 Teaching CS 307, an introduction to machine learning for data science students.
 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 might have a work phone, but I honestly don’t know the number and I respond faster to email anyway.
 Email: dalpiaz2@illinois.edu
 Office: 2320 Siebel Center for Computer Science
 GitHub: daviddalpiaz
Posts

20231114 Careers in Sports & Data

20230330 Moneyball in R

20230209 Reduce Friction, Increase Learning

20221004 Accessing Baseball Data for Analysis with R

20220402 Recreating NFL Scorigami with R

20200817 Ten Simple Rules for Success in STAT 432

20191127 Letters of Recommendation

20190822 The Extended Syllabus
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Teaching
CS 307
Modeling and Learning in Data ScienceCS 498
EndtoEnd Data ScienceSTAT 100
StatisticsSTAT 200
Statistical AnalysisSTAT 385
Statistical Programming MethodsSTAT 400
Statistics and Probability ISTAT 420
Statistical Modeling in RSTAT 432
Basics of Statistical LearningSTAT 510
Mathematical StatisticsSTAT 593
Statistics InternshipSTAT 3202 @ OSU
Statistical InferenceSTAT 4194 @ OSU
Data Analytics Capstone
Books
 Atomic R
 Currently in use for STAT 385 at Illinois for the Department of Statistics. Provides an introduction to programming through the use of the R programming language. Focuses on “Base R” rather than the
tidyverse
collection of domain specific packages.
 Currently in use for STAT 385 at Illinois for the Department of Statistics. Provides an introduction to programming through the use of the R programming language. Focuses on “Base R” rather than the
 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
 These books should largely be considered abandonware. Expect to see similar material for Python developed for use in CS 307.
 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.