Statistics Program

The Five College Statistics Program was created in 2011 to enable statistics faculty members at the five campuses to coordinate and integrate resources to better serve our statistics and data science students.

“Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, the courage to predict the things we can, and the wisdom to know the difference.”   - Nate Silver (Five Thirty Eight), The Signal and the Noise: Why So Many Predictions Fail - But Some Don't

"Statisticians now collaborate with the scientists generating the data to develop innovative new theory and methods to tackle problems never envisioned." Marie Davidian (North Carolina State University)

"Data is the sword of the 21st century, those who wield it well, the Samurai."
- Jonathan Rosenberg  (former Google Inc. Senior Vice President)

The time to become statistically literate is now. The Five College Statistics Program was created in 2011 to enable statistics faculty members at the five campuses to coordinate and integrate resources to better serve our statistics and data science students.

Whether you want to take an introductory statistics or data science class or pursue elective course offerings, the Five Colleges has courses and programs of study just waiting for you.  There are undergraduate majors in statistics and data science at Smith, Mount Holyoke, and Amherst Colleges, undergraduate and graduate programs at the University of Massachusetts, and growth in faculty staffing and enrollments at all of the institutions that make up the Five Colleges.

On this page, you can find resources, including links to statistics courses at each school, statistics faculty on each campus, news and events, announcements and more.

The Five College Statistics Program is committed to fostering closer ties between the faculty members teaching statistics and facilitating additional curricular cooperation to continue the strong statistical presence in the Valley. The Five College Statisticians meet on a regular basis to coordinate activities and curricular offerings.

On This Page

News

Nicholas J. Horton, the Beitzel Professor in Technology and Society (Statistics and Data Science) at Amherst College, has been selected as the recipient of the 2023 Mosteller Statistician of the Year award by the Boston Chapter of the American Statistical Association. The award honors individuals from academia, industry, and government who have made exceptional contributions to the field of statistics and who have shown outstanding service to the statistical community, including the Boston Chapter.

Winners of the Five College Statistics award for 2023 are: 

  • Amherst: Elizabeth Williamson and Alex Brandfonbrener
  • Hampshire: Sabina Iftikhar
  • Mt Holyoke: Emily Rosaci
  • Smith: Clara Li  and Aushanae Haller
  • UMass/Biostatistics: Benjamin Goldberg
  • UMass/Statistics: Adira Cohen

Congratulations to all of these students for their excellent work!

Professor Brittney Bailey (Amherst College) was named the recipient of the 2023 Mu Sigma Rho Early Career Undergraduate Impact Award for her dedicated and innovative approaches to support and empower students through her teaching, her leadership of StatFest and The STEM Incubator, and her efforts on behalf of the profession. More information about the award can be found at: https://www.stat.purdue.edu/msr/

 

Professor Nick Horton, Beitzel Professor of Technology and Society (Statistics and Data Science), Department of Mathematics and Statistics, Amherst College, has been elected as vice president of the American Statistical Association (ASA). Professor Horton's term begins in January 2021; he will serve with ASA president-elect Dionne Price, who will become the first African-American president of the ASA.

Professor Miles Ott, Assistant Professor of Statistical and Data Sciences is the 2021 LGBTQ+ Educator of the Year. This award is given an educator for significant impact on STEM students "through teaching, advocacy, and role modeling."

Congratulations to Professor Ott on this honor!

The Five Colleges had a strong showing in the Fall 2020 Undergraduate Statistics Project Competition, with winners in the Electronic Undergraduate Statistics Research Conference (eUSR), the Undergraduate Statistics Class Project (USCLAP), and the Undergraduate Statistics Research Project (USRESP).

Congratulations to our Fall 2020 competition winners:

Nicholas Reich, Associate Professor of Biostatistics, recently delivered a series of keynote talks on the topic of COVID-19 forecasting

Thank you, Professor Reich, for your continuing contributions to the field of Biostatistics!

Courses

Note that if you don't see classes from all campuses currently listed, they will appear as the campuses release their course schedules for the semester. The five campuses release their schedules on different dates. Visit this page for specific dates.

Spring 2024 Statistics Courses

Subject Course # Sect # Course Title Instructor(s) Institution Meeting Times
STAT 136 01 Stats and Mental Health Shu-Min Liao Amherst College TU/TH | 8:30 AM - 9:50 AM
STAT 200 01 Health Injustice Pamela Matheson Amherst College M/W | 2:00 PM - 3:20 PM
STAT 230 01 Intermediate Stats Pamela Matheson Amherst College M/W/F | 11:00 AM - 11:50 AM
STAT 230 02 Intermediate Stats Pamela Matheson Amherst College M/W/F | 12:00 PM - 12:50 PM
STAT 231 01 Data Science Amy Wagaman Amherst College M/W | 8:30 AM - 9:50 AM
STAT 231 02 Data Science Nicholas Horton Amherst College TU/TH | 1:00 PM - 2:20 PM
STAT 325 01 Text Analytics Nicholas Horton Amherst College TU/TH | 2:30 PM - 3:50 PM
STAT 370 01 Theoretical Statistics Amy Wagaman Amherst College M/W/F | 12:00 PM - 12:50 PM
DATA 113 01 Intro to Data Science Kenneth Mulder Mount Holyoke College MWF 08:30AM-09:45AM
DATA 390 01 Data Science Capstone Kenneth Mulder Mount Holyoke College TTH 09:00AM-10:15AM
STAT 140 01 Intro Ideas/Applic Statistics Tori Day Mount Holyoke College MWF 10:00AM-11:15AM
STAT 140 02 Intro Ideas/Applic Statistics Tori Day Mount Holyoke College MWF 01:45PM-03:00PM
STAT 140 03 Intro Ideas/Applic Statistics Tori Day Mount Holyoke College MWF 03:15PM-04:30PM
STAT 140 04 Intro Ideas/Applic Statistics Jing Li,Gary Gillis Mount Holyoke College TTHF 01:45PM-03:00PM;F 01:45PM-03:00PM
STAT 242 01 Intermediate Statistics Isabelle Beaudry Mount Holyoke College MWF 08:30AM-09:45AM
STAT 244NF 01 Infectious Disease Modeling Marie Ozanne Mount Holyoke College TTH 10:30AM-11:45AM
STAT 244NF 02 Infectious Disease Modeling Marie Ozanne Mount Holyoke College TTH 01:45PM-03:00PM
STAT 340 01 Applied Regression Methods Isabelle Beaudry Mount Holyoke College MWF 10:00AM-11:15AM
STAT 343 01 Mathematical Statistics Laurie Tupper Mount Holyoke College MWF 01:45PM-03:00PM
STAT 344TM 01 Time Series Analysis Laurie Tupper Mount Holyoke College MWF 03:15PM-04:30PM
SDS 100 01 Lab: Computing w/Data Justin Baumann Smith College TU 9:25 AM - 10:40 AM
SDS 100 02 Lab: Computing w/Data Justin Baumann Smith College TU 10:50 AM - 12:05 PM
SDS 100 03 Lab: Computing w/Data Justin Baumann Smith College TU 1:20 PM - 2:35 PM
SDS 100 04 Lab: Computing w/Data Robin Livingston Smith College TU 1:20 PM - 2:35 PM
SDS 100 05 Lab: Computing w/Data Robin Livingston Smith College TU 2:45 PM - 4:00 PM
SDS 100 06 Lab: Computing w/Data Robin Livingston Smith College TU 4:10 PM - 5:25 PM
SDS 100 07 Lab: Computing w/Data Clara Rosenberg Smith College TU 2:45 PM - 4:00 PM
SDS 100 08 Lab: Computing w/Data Clara Rosenberg Smith College TU 4:10 PM - 5:25 PM
SDS 100 09 Lab: Computing w/Data Clara Rosenberg Smith College TU 5:35 PM - 6:50 PM
SDS 192 01 Intro to Data Sciences Shiya Cao Smith College M W F 9:25 AM - 10:40 AM
SDS 192 02 Intro to Data Sciences Nicholas Schwab Smith College M W F 10:50 AM - 12:05 PM
SDS 201 01 Statistical Methods:Undergrad William Hopper Smith College M W F 10:50 AM - 12:05 PM
SDS 220 01 Intro/Probability/Statistics Albert Y. Kim Smith College M W F 8:00 AM - 9:15 AM
SDS 220 02 Intro/Probability/Statistics Nicholas Schwab Smith College M W F 9:25 AM - 10:40 AM
SDS 220 03 Intro/Probability/Statistics Rebecca Kurtz-Garcia Smith College W F 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
SDS 270 01 Programming Data Science: R William Hopper Smith College M W F 8:00 AM - 9:15 AM
SDS 290 01 Research Design & Analysis Randi L Garcia Smith College TU TH 10:50 AM - 12:05 PM
SDS 291 01 Multiple Regression William Hopper Smith College W F 1:20 PM - 2:35 PM
SDS 291 02 Multiple Regression Kaitlyn Cook Smith College TU TH 9:25 AM - 10:40 AM
SDS 293 01 Modeling for Machine Learning Albert Y. Kim Smith College M W 10:50 AM - 12:05 PM
SDS 300cr 01 Sem:T-Coral Reef Justin Baumann Smith College M W 9:25 AM - 10:40 AM
SDS 320 01 Mathematical Statistics Rebecca Kurtz-Garcia Smith College W F 2:45 PM - 4:00 PM
SDS 390be 01 T-Biostatistics&Epidemiology Kaitlyn Cook Smith College TU TH 1:20 PM - 2:35 PM
SDS 410 01 Capstone in SDS Shiya Cao Smith College W F 1:20 PM - 2:35 PM
PUBHLTH 223 01 Intro/Biostats for PUBHLTH Scott Chasan-Taber UMass Amherst M W F 9:05AM 9:55AM
PUBHLTH 494CI 01 Public Health Sciences Capston Karl Cyr UMass Amherst TU TH 10:00AM 11:15AM
PUBHLTH 494CI 02 Public Health Sciences Capston Karl Cyr UMass Amherst TU TH 11:30AM 12:45PM
PUBHLTH 494CI 03 Public Health Sciences Capston KRYSTAL KITTLE UMass Amherst M W 2:30PM 3:45PM
PUBHLTH 494CI 04 Public Health Sciences Capston KRYSTAL KITTLE UMass Amherst M W 4:00PM 5:15PM
PUBHLTH 494CI 05 Public Health Sciences Capston David Chin UMass Amherst TU TH 1:00PM 2:15PM
SPHHS 616 01 Epidemiology & Biostatistics B Elizabeth Cook,Raji Balasubramanian UMass Amherst M W 2:30PM 3:45PM
STATISTC 310 01 Fundamental Concepts/Stats Qian Zhao UMass Amherst TU TH 10:00AM 11:15AM
STATISTC 315 01 Statistics I Yao Li UMass Amherst TU TH 10:00AM 11:15AM
STATISTC 315 02 Statistics I Wuzhe Xu UMass Amherst M W F 12:20PM 1:10PM
STATISTC 315 03 Statistics I Wuzhe Xu UMass Amherst M W F 1:25PM 2:15PM
STATISTC 315 04 Statistics I Yalin Rao UMass Amherst M W F 11:15AM 12:05PM
STATISTC 315 05 Statistics I Yao Li UMass Amherst TU TH 8:30AM 9:45AM
STATISTC 315 06 Statistics I Luc Rey-Bellet UMass Amherst TU TH 1:00PM 2:15PM
STATISTC 315 07 Statistics I Michael Sullivan UMass Amherst TU TH 2:30PM 3:45PM
STATISTC 516 01 Statistics II Theodore Westling UMass Amherst TU TH 11:30AM 12:45PM
STATISTC 516 02 Statistics II Sepideh Mosaferi UMass Amherst TU TH 10:00AM 11:15AM
STATISTC 516 03 Statistics II Theodore Westling UMass Amherst TU TH 2:30PM 3:45PM
STATISTC 516 04 Statistics II Sepideh Mosaferi UMass Amherst TU TH 1:00PM 2:15PM
STATISTC 525 01 Regression&Analysis/Variance Daeyoung Kim UMass Amherst M W F 10:10AM 11:00AM
STATISTC 525 02 Regression&Analysis/Variance Jonathan Larson UMass Amherst M W F 12:20PM 1:10PM
STATISTC 525 03 Regression&Analysis/Variance Yalin Rao UMass Amherst M W F 1:25PM 2:15PM
STATISTC 530 01 Analysis of Discrete Data Daeyoung Kim UMass Amherst M W F 12:20PM 1:10PM
STATISTC 535 01 Statistical Computing Carlos Soto UMass Amherst M W 2:30PM 3:45PM
STATISTC 598C 01 StatisticalConsultingPracticum Krista Gile,Anna Liu UMass Amherst W 8:40AM 9:55AM

Resources

The Lorna M. Peterson Award supports scholarly and creative work by undergraduate students taking part in Five College programs. The prize is awarded annually based on nominations from Five College programs.

Campus Curricula

Contact Us

Five College Statistics Program Representatives:
 

Nicholas (Nick) Horton, Beitzel Professor in Technology and Society, Department of Mathematics and Statistics, Amherst College (Program Chair and Webmaster)

Jeffrey Barton, Professor of Mathematics, Hampshire College (Secretary/Treasurer)

Laurie Tupper, Associate Professor of Statistics, Mount Holyoke College

Randi Garcia, Assistant Professor of Psychology and of Statistical & Data Sciences, Smith College 

Chi Hyun Lee, Assistant Professor of Biostatistics, UMass

Carlos Soto, Assistant Professor of Mathematics and Statistics, UMass
 

Five College Staff Liaison:
 

Ray Rennard, Director of Academic Programs