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.

    Fall 2023 Statistics Courses

    Subject Course # Sect # Course Title Instructor(s) Institution Meeting Times
    MATH 135 01 Intro to Stats Modeling Pamela Matheson Amherst College M/W/F | 9:00 AM - 9:50 AM
    MATH 135 02 Intro to Stats Modeling Pamela Matheson Amherst College M/W/F | 10:00 AM - 10:50 AM
    MATH 135 03 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 11:00 AM - 11:50 AM
    MATH 135 04 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 2:00 PM - 2:50 PM
    MATH 360 01 Probability Nicholas Horton Amherst College TU/TH | 2:30 PM - 3:50 PM
    MATH 360 02 Probability Katherine Moore Amherst College M/W/F | 11:00 AM - 11:50 AM
    STAT 108 01 Stat Ethics Institutions Andreas Georgiou Amherst College TH | 2:30 PM - 5:15 PM
    STAT 111 01 Intro Stats Pamela Matheson Amherst College M/W/F | 1:00 PM - 1:50 PM
    STAT 135 01 Intro to Stats Modeling Pamela Matheson Amherst College M/W/F | 9:00 AM - 9:50 AM
    STAT 135 02 Intro to Stats Modeling Pamela Matheson Amherst College M/W/F | 10:00 AM - 10:50 AM
    STAT 135 03 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 11:00 AM - 11:50 AM
    STAT 135 04 Intro to Stats Modeling Kevin Donges Amherst College M/W/F | 2:00 PM - 2:50 PM
    STAT 225 01 Nonparametric Statistics Amy Wagaman Amherst College M/W/F | 1:00 PM - 1:50 PM
    STAT 230 01 Intermediate Stats Shu-Min Liao Amherst College TU/TH | 8:30 AM - 9:50 AM
    STAT 230 02 Intermediate Stats Shu-Min Liao Amherst College TU/TH | 11:30 AM - 12:50 PM
    STAT 231 01 Data Science Katharine Correia Amherst College TU/TH | 10:00 AM - 11:20 AM
    STAT 231 02 Data Science Nicholas Horton Amherst College TU/TH | 1:00 PM - 2:20 PM
    STAT 360 01 Probability Nicholas Horton Amherst College TU/TH | 2:30 PM - 3:50 PM
    STAT 360 02 Probability Katherine Moore Amherst College M/W/F | 11:00 AM - 11:50 AM
    STAT 404 01 Missing Data Katharine Correia Amherst College TU/TH | 1:00 PM - 2:20 PM
    STAT 495 01 Advanced Data Analysis Amy Wagaman Amherst College M/W/F | 10:00 AM - 10:50 AM
    DATA 113 01 Intro to Data Science Kenneth Mulder Mount Holyoke College MWF 08:30AM-09:45AM
    DATA 113 02 Intro to Data Science Kenneth Mulder Mount Holyoke College MWF 10:00AM-11:15AM
    DATA 390 01 Data Science Capstone Kenneth Mulder Mount Holyoke College TTH 09:00AM-10:15AM
    STAT 140 01 Intro Ideas/Applic Statistics Laurie Tupper Mount Holyoke College MWF 08:30AM-09:45AM
    STAT 140 02 Intro Ideas/Applic Statistics Laurie Tupper Mount Holyoke College MWF 10:00AM-11:15AM
    STAT 140 03 Intro Ideas/Applic Statistics Alanna Hoyer-Leitzel Mount Holyoke College MWF 01:45PM-03:00PM
    STAT 140 04 Intro Ideas/Applic Statistics Alanna Hoyer-Leitzel Mount Holyoke College MWF 03:15PM-04:30PM
    STAT 242 01 Intermediate Statistics Isabelle Beaudry Mount Holyoke College MWF 10:00AM-11:15AM
    STAT 242 02 Intermediate Statistics Carrie Hosman Mount Holyoke College TTH 10:30AM-11:45AM;F 01:30PM-02:45PM
    STAT 244MP 01 Survey Sampling Isabelle Beaudry Mount Holyoke College MWF 11:30AM-12:45PM
    STAT 340 01 Applied Regression Methods Laurie Tupper Mount Holyoke College MWF 01:45PM-03:00PM
    MTH 246 01 Probability Kaitlyn Cook Smith College TU TH 10:50 AM - 12:05 PM
    PSY 364 01 Research Sem: Intrgrp Relatnsh Randi L Garcia Smith College M W 10:50 AM - 12:05 PM
    SDS 100 01 Lab: Computing w/Data Casey Berger Smith College TU 8:00 AM - 9:15 AM
    SDS 100 02 Lab: Computing w/Data Casey Berger Smith College TU 9:25 AM - 10:40 AM
    SDS 100 03 Lab: Computing w/Data Casey Berger Smith College TU 10:50 AM - 12:05 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 5:35 PM - 6:50 PM
    SDS 100 08 Lab: Computing w/Data Clara Rosenberg Smith College TU 7:00 PM - 8:15 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 192 03 Intro to Data Sciences Nicholas Schwab Smith College W F 1:20 PM - 2:35 PM; M 1:40 PM - 2:55 PM
    SDS 201 01 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 Rebecca Kurtz-Garcia Smith College M W F 9:25 AM - 10:40 AM
    SDS 220 02 Intro/Probability/Statistics Rebecca Kurtz-Garcia Smith College M W F 10:50 AM - 12:05 PM
    SDS 220 03 Intro/Probability/Statistics Nicholas Schwab Smith College W F 2:45 PM - 4:00 PM; M 3:05 PM - 4:20 PM
    SDS 237 01 Data Ethnography Lindsay Poirier Smith College TU TH 9:25 AM - 10:40 AM
    SDS 270 01 Adv Programming-Data Science William Hopper Smith College W F 2:45 PM - 4:00 PM; M 3:05 PM - 4:20 PM
    SDS 271 01 Program/Data Science: Python Casey Berger Smith College TU TH 2:45 PM - 4:00 PM
    SDS 291 01 Multiple Regression Kaitlyn Cook Smith College TU TH 9:25 AM - 10:40 AM
    SDS 291 02 Multiple Regression Scott J. LaCombe Smith College TU TH 2:45 PM - 4:00 PM
    SDS 300di 01 Sem:T-Disability,Inclusn&Data Shiya Cao Smith College W F 1:20 PM - 2:35 PM
    SDS 364 01 Research Sem: Intrgrp Relatnsh Randi L Garcia Smith College M W 10:50 AM - 12:05 PM
    SDS 390ef 01 T-Ecological Forecasting Albert Y. Kim Smith College TU TH 9:25 AM - 10:40 AM
    SDS 410 01 Sem: Capstone in SDS Albert Y. Kim Smith College TU TH 1:20 PM - 2:35 PM
    BIOSTATS 530 01 Intro/Stat Computing with R Raji Balasubramanian UMass Amherst TU TH 8:30AM 9:45AM
    BIOSTATS 531 01 IntermediateStatComp/DataSci R Raji Balasubramanian UMass Amherst TU TH 8:30AM 9:45AM
    PUBHLTH 223 01 Intro/Biostats for PUBHLTH Scott Chasan-Taber UMass Amherst M W F 9:05AM 9:55AM
    PUBHLTH 460 01 TellingStories/DataStatModelVi Nicholas Reich UMass Amherst TU TH 10:00AM 11:15AM
    STATISTC 310 01 Fundamental Concepts/Stats Haben Michael UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 310 02 Fundamental Concepts/Stats Haben Michael UMass Amherst TU TH 1:00PM 2:15PM
    STATISTC 501 01 Meth Applied Stats Joanna Jeneralczuk UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 515 01 Statistics I Wei Zhu UMass Amherst M W 2:30PM 3:45PM
    STATISTC 515 02 Statistics I Carlos Soto UMass Amherst M W F 11:15AM 12:05PM
    STATISTC 515 03 Statistics I Lulu Kang UMass Amherst M W F 10:10AM 11:00AM
    STATISTC 515 04 Statistics I Michael Sullivan UMass Amherst TU TH 2:30PM 3:45PM
    STATISTC 515 05 Statistics I Michael Sullivan UMass Amherst TU TH 4:00PM 5:15PM
    STATISTC 515 06 Statistics I Wei Zhu UMass Amherst M W 4:00PM 5:15PM
    STATISTC 516 01 Statistics II Sepideh Mosaferi UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 516 02 Statistics II Sepideh Mosaferi UMass Amherst TU TH 1:00PM 2:15PM
    STATISTC 516 03 Statistics II Jonathan Larson 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 Daeyoung Kim UMass Amherst M W 2:30PM 3:45PM
    STATISTC 535 01 Statistical Computing Maryclare Griffin UMass Amherst TU TH 11:30AM 12:45PM
    STATISTC 535 02 Statistical Computing Shai Gorsky UMass Amherst W 6:00PM 8:30PM
    STATISTC 590C 01 Intro to Causal Inference Theodore Westling UMass Amherst TU TH 1:00PM 2:15PM
    STATISTC 598C 01 StatisticalConsultingPracticum Anna Liu,Krista Gile UMass Amherst W 12:20PM 1:35PM
    STATISTC 607 01 Math Statistics I John Staudenmayer UMass Amherst M W F 10:10AM 11:00AM
    STATISTC 607 02 Math Statistics I Hyunsun Lee UMass Amherst M 6:00PM 8:30PM
    STATISTC 625 01 Regression Modeling Krista Gile UMass Amherst M W 2:30PM 3:45PM
    STATISTC 625 02 Regression Modeling Shai Gorsky UMass Amherst TU 6:00PM 8:30PM
    STATISTC 631 01 Categorical Data Analysis Zijing Zhang UMass Amherst TH 6:00PM 8:30PM
    STATISTC 639 01 Time Series Analysis and Appl Haben Michael UMass Amherst TU TH 4:00PM 5:15PM
    STATISTC 691P 01 S-Project Seminar Erin Conlon UMass Amherst SA 1:00PM 3:30PM
    STATISTC 705 01 Linear Models I John Staudenmayer UMass Amherst M W F 11:15AM 12:05PM
    Course Lists From Previous Semesters

    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:
     

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

    Brian Schultz, Professor of Entomology and Ecology, Hampshire College

    Laurie Tupper, Associate Professor of Statistics, Mount Holyoke College

    Scott LaCombe, Assistant Professor of Government and of Statistical & Data Sciences, Smith College (Secretary/Treasurer)

    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