Authored by
Jessica Kraker
Title

Prof. Jessica Kraker, Ph.D.

Pronouns
she / her
Placeholder for titles
Professor
Content type
College of Arts and Sciences
Mathematics Department

Contact Information

Office
Hibbard Humanities Hall 517
124 Garfield Ave
Eau Claire, WI 54701
Phone
715-836-2537
Email
Hours
Online: Zoom from 2-3 on Monday and Thursday
In-person: 12-12:50 Thursday and 8-9am Friday in Math Lab; 10-10:50am Friday in HHH 407
Student-Research day: Wednesdays
ID
Travels on Sabbatical (in-progress) Faculty page with links (in-progress) Notes: Basics of Data Analysis in R (in-progress) Introduction to R Tutorial Historic Work Summary Historic COVID dashboard a fun Modeling Question a fun Sierpinski Triangle app Local Humidity / Climate data (in-progress)
Biography

Biography

I am Dr. Jessica Kraker, aka Prof. Jessica. I received my undergraduate degree in mathematics (with minors in statistics and chemistry), and I then earned my PhD in Statistics from the University of Minnesota - Twin Cities.

In my professional life, I have been teaching at UW - Eau Claire since 2006, covering courses in undergraduate statistics (introductory and upper-level) and Master’s-level data mining and programming. My research is in data-mining techniques, with a focus on penalized regression. My recent (last ~ 6 years) work has been centered on time series and sports analytics.

In my personal life, I enjoy being outdoors as much as I can, and you will often find me out on the trails with my dog. Family time, running, and volunteering are all important parts of my balance.

Preferred contact via university email: krakerjj@uwec.edu.
 

Education

Education

  • Ph.D., University of Minnesota - Twin Cities (Statistics)
  • M.S., University of Minnesota - Twin Cities (Statistics)
  • B.A., University of Minnesota - Morris (Mathematics) 
Teaching and Research Interests

Teaching and Research Interests

  • Updating, teaching, developing, and fine-tuning course material on a variety of statistical topics.
  • Introducing and advancing usage of the R programming language, across disciplines.
  • Initiating and participating in interdisciplinary conversations and collaborations.
  • Supporting university endeavors via departmental support, curricular development (via committee service), and summer teaching.
  • Contributing to the larger statistical community via speaking and written contributions.
  • Mentoring student-faculty research projects within statistics and sports analytics.  
  • Areas of research activity include: Penalized Regression; Cross-validation; Data Mining; Sports Analytics; Time Series.