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

    Faculty

    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!

    Events

    Recurring Events

    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 2025 Statistics Courses

    Subject Course # Sect # Course Title Instructor(s) Institution Meeting Times
    STAT 135 01 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 1:00 PM - 1:50 PM
    STAT 135 02 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 2:00 PM - 2:50 PM
    STAT 135 03 Intro to Stats Modeling Shu-Min Liao Amherst College TU/TH | 8:30 AM - 9:50 AM
    STAT 135 04 Intro to Stats Modeling Brittney Bailey Amherst College TU/TH | 2:30 PM - 3:50 PM
    STAT 136 01 Stats and Mental Health Shu-Min Liao Amherst College TU/TH | 11:30 AM - 12:50 PM
    STAT 201 01 Writing in STEM Katharine Correia Amherst College TU/TH | 1:00 PM - 2:20 PM
    STAT 230 01 Intermediate Stats Pamela Matheson Amherst College M/W/F | 10:00 AM - 10:50 AM
    STAT 230 02 Intermediate Stats Pamela Matheson Amherst College M/W/F | 11:00 AM - 11:50 AM
    STAT 231 01 Data Science Nicholas Horton Amherst College TU/TH | 2:30 PM - 3:50 PM
    STAT 231 02 Data Science Katharine Correia Amherst College TU/TH | 10:00 AM - 11:20 AM
    STAT 360 01 Probability Kevin Donges Amherst College M/W/F | 10:00 AM - 10:50 AM
    STAT 370 01 Theoretical Statistics Amy Wagaman Amherst College M/W/F | 11:00 AM - 11:50 AM
    STAT 456 01 Generalized Lin Models Brittney Bailey Amherst College TU/TH | 1:00 PM - 2:20 PM
    NS 0104 1 Introduction to Data Science Kenneth Mulder Hampshire College 10:30AM-11:50AM TU;10:30AM-11:50AM TH
    NS 0259 1 Intro to Beyesian Modeling Kenneth Mulder Hampshire College 01:00PM-02:20PM M;01:00PM-02:20PM W
    DATA 113 01 Intro to Data Science Arie Shaus Mount Holyoke College MWF 11:30AM-12:45PM
    DATA 390 01 Data Science Capstone Arie Shaus Mount Holyoke College MW 10:00AM-11:15AM
    STAT 140 01 Intro Ideas/Applic Statistics Ishfaaq Mohammed Imtiyas Mount Holyoke College MWF 08:30AM-09:45AM
    STAT 140 02 Intro Ideas/Applic Statistics Ishfaaq Mohammed Imtiyas Mount Holyoke College MWF 10:00AM-11:15AM
    STAT 140 03 Intro Ideas/Applic Statistics Ben Pittman-Polletta Mount Holyoke College MWF 01:45PM-03:00PM
    STAT 242 01 Intermediate Statistics Isabelle Beaudry Mount Holyoke College MWF 10:00AM-11:15AM
    STAT 242 02 Intermediate Statistics Laura Lyman Mount Holyoke College MWF 03:15PM-04:30PM
    STAT 244SC 01 Computational Statistics Laura Lyman Mount Holyoke College MW 01:45PM-03:00PM
    STAT 340 01 Applied Regression Methods Ishfaaq Mohammed Imtiyas Mount Holyoke College MWF 03:15PM-04:30PM
    STAT 343 01 Mathematical Statistics Isabelle Beaudry Mount Holyoke College MWF 08:30AM-09:45AM
    STAT 344ND 01 Analysis of Neural Data Ben Pittman-Polletta Mount Holyoke College MW 10:00AM-11:15AM
    BIO 372 01 Colq:Quantitativ Ecology Aly Putnam Smith College M W 10:50 AM - 12:05 PM
    SDS 100 01 Lab: Computing w/Data yujie wang Smith College TU 8:00 AM - 9:15 AM
    SDS 100 02 Lab: Computing w/Data yujie wang Smith College TU 9:25 AM - 10:40 AM
    SDS 100 03 Lab: Computing w/Data yujie wang Smith College TU 10:50 AM - 12:05 PM
    SDS 109 01 Communicating With Data Ab Mosca Smith College TU TH 1:20 PM - 2:35 PM
    SDS 192 01 Intro to Data Sciences Nicholas Schwab 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 Kementari Whitcher Smith College M W F 9:25 AM - 10:40 AM
    SDS 201 02 Statistical Methods:Undergrad William Hopper Smith College W F 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
    SDS 220 01 Intro/Probability/Statistics Kaitlyn Cook Smith College M W F 10:50 AM - 12:05 PM
    SDS 220 02 Intro/Probability/Statistics Rebecca Kurtz-Garcia Smith College W F 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
    SDS 236 01 Data Journalism Ben Baumer,Naila F. Moreira Smith College TU TH 1:20 PM - 2:35 PM
    SDS 237 01 Data Ethnography Lindsay Poirier Smith College M W 9:25 AM - 10:40 AM
    SDS 238 01 Community-Based Data Science Lindsay Poirier Smith College M W 10:50 AM - 12:05 PM
    SDS 270 01 Programming Data Science: R William Hopper Smith College M W 8:00 AM - 9:15 AM
    SDS 290 01 Research Design & Analysis Scott J. LaCombe Smith College TU TH 2:45 PM - 4:00 PM
    SDS 291 01 Multiple Regression Kaitlyn Cook Smith College M W 9:25 AM - 10:40 AM
    SDS 291 02 Multiple Regression yujie wang Smith College W 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
    SDS 293 01 Machine Learning R. Jordan Crouser Smith College TU TH 1:20 PM - 2:35 PM
    SDS 300fs 01 Sem: T-Food Systems Kementari Whitcher Smith College W 2:45 PM - 4:00 PM; M 3:05 PM - 4:20 PM
    SDS 320 01 Mathematical Statistics Rebecca Kurtz-Garcia Smith College W 2:45 PM - 4:00 PM; M 3:05 PM - 4:20 PM
    SDS 364 01 Research Sem: Intrgrp Relatnsh Randi L Garcia Smith College TU TH 10:50 AM - 12:05 PM
    SDS 390cd 01 T-Categorical Data Kementari Whitcher Smith College M W 10:50 AM - 12:05 PM
    SDS 410 01 Capstone in SDS Ben Baumer Smith College W 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
    BIOSTATS 683 01 Intro to Causal Inference Aaron Sarvet UMass Amherst M W 2:30PM 3:45PM
    BIOSTATS 748 01 Applied Survival Analysis Raji Balasubramanian UMass Amherst TU TH 11:30AM 12:45PM
    PUBHLTH 223 01 Intro/Biostats for PUBHLTH Sofija Zagarins UMass Amherst M W F 11:15AM 12:05PM
    PUBHLTH 494CI 01 Public Health Sciences Capston Karl Cyr UMass Amherst TU TH 4:00PM 5:15PM
    PUBHLTH 494CI 02 Public Health Sciences Capston Song Liang UMass Amherst TU TH 1:00PM 2:15PM
    PUBHLTH 494CI 03 Public Health Sciences Capston David Chin UMass Amherst TU TH 10:00AM 11:15AM
    PUBHLTH 494CI 04 Public Health Sciences Capston KRYSTAL KITTLE UMass Amherst M W 2:30PM 3:45PM
    SPHHS 616 01 Epidemiology & Biostatistics B Elizabeth Cook,Sofija Zagarins UMass Amherst M W 2:30PM 3:45PM
    STATISTC 310 01 Fundamental Concepts/Stats Sepideh Mosaferi UMass Amherst TU TH 10:00AM 11:15AM
    STATISTC 315 01 Statistics I Michael Sullivan UMass Amherst TU TH 10:00AM 11:15AM
    STATISTC 315 02 Statistics I Byeong-Ho Bahn UMass Amherst M W F 12:20PM 1:10PM
    STATISTC 315 03 Statistics I Qian-Yong Chen UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 315 04 Statistics I UMass Amherst M W F 11:15AM 12:05PM
    STATISTC 315 05 Statistics I Michael Sullivan UMass Amherst TU TH 8:30AM 9:45AM
    STATISTC 315 06 Statistics I Kien Nguyen UMass Amherst TU TH 1:00PM 2:15PM
    STATISTC 315 07 Statistics I Luc Rey-Bellet UMass Amherst TU TH 2:30PM 3:45PM
    STATISTC 516 01 Statistics II Sepideh Mosaferi UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 516 03 Statistics II UMass Amherst TU TH 2:30PM 3:45PM
    STATISTC 516 04 Statistics II UMass Amherst M W F 12:20PM 1:10PM
    STATISTC 525 01 Regression&Analysis/Variance Jonathan Larson 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 Daeyoung Kim UMass Amherst M W F 11:15AM 12:05PM
    STATISTC 530 01 Analysis of Discrete Data UMass Amherst M W F 12:20PM 1:10PM
    STATISTC 535 01 Statistical Computing Maryclare Griffin UMass Amherst M W 2:30PM 3:45PM
    STATISTC 598C 01 StatisticalConsultingPracticum Krista Gile,Anna Liu UMass Amherst TU 1:00PM 2:15PM
    Course Lists From Previous Semesters
    Statistics Regularly Offered Course List

    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

    Amherst College (Major)
    Hampshire College (Academic Philosophy)
    Mount Holyoke College (Major and Minor)
    Smith College (Major and Minor)
    UMass Amherst (Undergraduate Program)

    Other Resources

    American Statistical Association (ASA)
    This Is Statistics
    UMass Amherst Statistics
    UMass Amherst Department of Biostatistics
    DSC-WAV (Wrangle-Analyze-Visualize) Project
    CAUSEweb
    Five College Statistics on Twitter

    Contact Us

    Five College Statistics Program Representatives:

    Amy Wagaman, Professor of Mathematics and Statistics, Amherst College (Chair)

    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 

    Carlos Soto, Assistant Professor of Mathematics and Statistics, UMass
     

    Five College Staff Liaison:
     

    Ray Rennard, Director of Academic Programs