
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.
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:
- Amelia Tran (Mount Holyoke) - eUSR Best Video Presentation
- Xian Ye, Hannah Snell, Dianne Caravela, and Natalia Iannucci (Smith) - USCLAP First Standing in Intermediate Statistics
- Juliet Ramey-Lariviere, Ivy Chen, and Kathleen Hablutzel (Smith) - USCLAP Honorable Mention in Intermediate Statistics
- Tyler Marshall (Amherst) - USRESP Third Standing
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.
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 |
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)
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