CIR Consultants & Hours

Center for Interdisciplinary Research
CIR Consultants & Hours

Statistics students who are Fellows in the Center for Interdisciplinary Research hold office hours for statistical consulting in Regents 207 (the CIR office). Consulting hours are on Sundays through Fridays. To meet the consultants please choose the CIR Fellow listed to the right.
Any faculty member or staff member who has questions about statistics related to their research or other work are welcome to drop-in during office hours. You may also refer students who are working on independent research projects, capstone projects, or semester-long class projects to visit with data analysis questions. Please note, however, that by the terms of our grant from the NSF, the CIR Fellows cannot provide tutoring assistance; students with statistical questions from regular coursework should contact the Academic Support Center or visit the stat help clinics instead.

Andrew Noecker ’23
Majors: Mathematics
Concentration: Statistics and Data Science
Statistics courses taken: Stat 212 – Statistics for the Sciences, Stat 272 – Statistical Modeling, Stat 316 – Advanced Statistical Modeling, MSCS 264 – Introduction to Data Science, MSCS 341 – Algorithms for Decision Making
Statistical Software Knowledge: R studio; Python; Tableau, SQL, Excel
My favorite thing about Stats and Data Science: Being able to apply my skills with data to a vast amount of outside areas.
The best insight I was ever given about Stats and Data Science: Document your data, you’ll thank yourself later

Pavel Makouski ’23
Major: Political Science
Concentrations: Statistics and Data Science; International Relations; Nordic Studies
Statistics courses taken: Stat 212 – Statistics for the Sciences, Stat 272 – Statistical Modeling, MSCS 264 – Introduction to Data Science, MSCS 341 – Algorithms for Decision Making
Statistical Software Knowledge: R
My favorite thing about Stats and Data Science: The community.
The best insight I was ever given about Stats and Data Science: You should not trust statisticians because they are always plotting something.

Meg Prapatthong ’23
Major: Quantitative Economics
Concentration: Statistics and Data Science
Statistics courses taken: Stat 272 – Statistical Modeling, Stat 282 – High Dimensional Data Analysis, Stat 316 – Advanced Statistical Modeling, MSCS 264 – Introduction to Data Science, ECON 260 – Intro to Economometrics
Statistical Software Knowledge: R, Excel, VBA
My favorite thing about Stats and Data Science: I like how we can use stats to apply in any field.
The best insight I was ever given about Stats and Data Science: Stackoverflow is your best friend

The best insight I was ever given about Stats and Data Science: When in doubt, Google it.

Rohan Silbaugh ’23
Major: Quantitative Economics
Concentration: Statistics and Data Science
Statistics courses taken: Stat 272 – Statistical Modeling, ECON 260 – Introductory Econometrics
Statistical Software Knowledge: R, R-Studio
My favorite thing about Stats and Data Science: The ability to gain insights into the world around me and how it works.
The best insight I was ever given about Stats and Data Science: Errors and debugging code should be expected and are part of the learning process!

Julia Cordes ’23
Major: Mathematics
Concentration: Statistics and Data Science, Mathematical Biology, Gender and Sexuality Studies
Statistics courses taken: Stat 212 – Statistics for the Sciences; Stat 272 – Statistical Modeling, MSCS 264 – Introduction to Data Science, MSCS 341 – Algorithms for Decision Making
Statistical Software Knowledge: R
My favorite thing about Stats and Data Science: Getting to answer fun questions about anything and everything.
The best insight I was ever given about Stats and Data Science: Google is a wonderful resource.

Rachel Stumpf ’24
Major: Majors: Mathematics, Kinesiology
Concentrations: Stats and Data Science, Ethnic Studies
Statistics courses taken: Stat 272 – Statistical Modeling, Stat 282 – Top: Spatial Data Analysis, Stat 316 – Advanced Statistical Modeling, MSCS 264 – Introduction to Data Science, MSCS 341 – Algorithms for Decision Making
Statistical Software Knowledge: R
My favorite thing about Stats and Data Science: Learning ways to explore and interpret data!
The best insight I was ever given about Stats and Data Science: To try every method and visualization of the data to see (un)expected results!

Taylor Smith ’23
Major: Biology
Concentrations: Statistics and Data Science, Neuroscience
Statistics courses taken: Stat 212 – Statistics for the Sciences; Stat 272 – Statistical Modeling; Stat 316 – Advanced Statistical Modeling; MSCS 264 – Introduction to Data Science; Stat 282 – Spatial Data Analysis
Statistical Software Knowledge: R studio
My favorite thing about Stats and Data Science: Getting to create visualizations of the data to show patterns in a data set!
The best insight I was ever given about Stats and Data Science: Be willing to ask for help if its is going to save you time and energy!

Nathaniel Mersy ’24
Major: Mathematics, Computer Science
Concentration: Statistics and Data Science
Statistics courses taken: Stat 272 – Statistical Modeling, Stat 316 – Advanced Statistical Modeling, MSCS 264 – Introduction to Data Science
Statistical Software Knowledge: R, Python
My favorite thing about Stats and Data Science: The ability to represent complicated data with simple visualizations.
The best insight I was ever given about Stats and Data Science: When in doubt, Google it.

Khang Vo Huynh ’23
Major: Mathematics, Computer Science
Concentration: Statistics and Data Science
Statistics courses taken: Stat 212 – Statistics for Science; MSCS 264 – Introduction to Data Science; MSCS 341 – Algorithms for Decision Making; MSCS 390 – Mathematics Practicum
Statistical Software Knowledge: R studio, MATLAB, Python
My favorite thing about Stats and Data Science: Exploratory data analysis and statistical machine learning.
The best insight I was ever given about Stats and Data Science: The key to a good model is explanatory data analysis.

Anja Logan ’24
Major: Mathematics, Computer Science
Concentrations: Statistics and Data Science
Statistics courses taken: Stat 272 – Statistical Modeling; MSCS 264 – Introduction to Data Science
Statistical Software Knowledge: R
My favorite thing about Stats and Data Science: Utilizing real world data to create visualizations!
The best insight I was ever given about Stats and Data Science: Make sure you understand the problem completely before jumping into the models or visualizations.

Maureen Wainwright ’23
Major: Political Science
Concentration: Statistics and Data Science, International Relations, Race and Ethnic Studies
Statistics courses taken: Stat 212 – Statistics for the Sciences; Stat 272 – Statistical Modeling; Stat 316 – Advanced Statistical Modeling; MSCS 264 – Introduction to Data Science
Statistical Software Knowledge: R studio, SPSS
My favorite thing about Stats and Data Science: Exploring real world research questions with data-based approach.
The best insight I was ever given about Stats and Data Science: Failure is a necessary step in the process of working through a problem. Keep trying.

Annika Cleven ’23
Major: Mathematics
Concentration: Statistics and Data Science, Mathematical Biology
Statistics courses taken: Stat 272 – Statistical Modeling; Stat 316 – Advanced Statistical Modeling; MSCS 264 – Introduction to Data Science; Spatial Statistics, High Dimensional Data Analysis
Statistical Software Knowledge: R, Python, Perl, Cytoscape
My favorite thing about Stats and Data Science: It is like a puzzle.
The best insight I was ever given about Stats and Data Science: To take every challenge at a time.

Upendo Laizer ’24
Major: Mathematics, Quantitative Economics
Concentrations: Statistics and Data Science
Statistics courses taken: Stat 272 – Statistical Modeling, MSCS 264 – Introduction to Data Science, MSCS 341 – Algorithms for Decision Making
Statistical Software Knowledge: Advanced in R
My favorite thing about Stats and Data Science: The amazing things that I learn from people when working in teams.
The best insight I was ever given about Stats and Data Science: A data scientist is not just a data scientist but a detective and a storyteller as well.

Cheng Vang ’24
Major: Mathematics
Concentrations: Statistics and Data Science
Statistics courses taken: Stat 110 – Principal of Statistics, MSCS 264 – Introduction to Data Science
Statistical Software Knowledge: R Studio; A little bit of Overleaf
My favorite thing about Stats and Data Science: To see the world in the eyes of data and numbers.
The best insight I was ever given about Stats and Data Science: How to read what lies within and with-out the data provided.