4:00 p.m.: Fengling Hu"A Visit to the Zoo: Teaching Machines to Think Like Humans"Advisor: Amy Wagaman4:50 p.m.: Robert Zielinski"A Comparison of Bayesian Inference Algorithms for Hierarchical Mixture Models:Advisor: Amy Wagaman5:40 p.m.: Zachary Brown"Using Em Methods to Handle Data Below the Lower Limit of Detection"Advisor: Nicholas Horton
Kate Finnerty: Wed, April 17
Ellie Thieu: Mon, April 22
Unless otherswise noted, department colloqia begin at 4:30 p.m. and are held in the Seeley Mudd building. Refreshments are served at 4:15 in SMUD 208.
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Dan Velleman
Professor Emeritus, Amherst College
"The Mystery of Colliding Blocks”
Thursday, March 12
4:00 p.m.*
Seeley Mudd 207
Abstract:
"I will solve a simple physics problem with a very surprising answer."
Nelis Potgieter, Assistant Professor of Mathematics, Texas Christian University
"Measurement Error Modeling Using Complex Data Transformations”
Thursday, March 12
4:30 p.m.
Seeley Mudd 206
Abstract:
Measurement error, formally defined as the difference between the measured value and the true value of a quantity of interest, is ubiquitous. When a doctor takes your blood pressure, the instrumentation may not be properly calibrated and the reading is subject to error. When completing an online Harry Potter Sorting Hat quiz, you may accidentally click the wrong option for a specific question and find yourself in House Slytherin! The effect of measurement error is sometimes insignificant, but there are instances where ignored measurement error can be rather consequential. You definitely do not want your doctor to put you on a long-term medication for managing high BP due to an erroneous measurement!
In this talk, I will discuss two problems frequently encountered when measurement error is present in sampled data. The first of these is known as density deconvolution, which involves estimating the density function of the population of interest. When measurement error is present, a density function estimated from the sample will have inflated variance, and interesting population features may be obscured. The second problem relates to regression modeling when the predictor variable is subject to measurement error. Here, when using the contaminated data to estimate the regression model, parameter estimates will be biased unless measurement error is properly adjusted for. I will show how the empirical phase functions, a transformation of the sample data to the complex plane, can be used to find solutions to both of these problems.
Oh, and don’t worry too much about your doctor unnecessarily prescribing blood pressure medication. She is well aware that measurement error exists, and will re-take the measurement, and also perform other tests before making a diagnosis. Being sorted into House Slytherin though, there you are on your own...
Michigan Calculus: Structure and Outcomes
Please join us to celebrate the end of another great semester!
Title: Symmetries, Groups, & How They Interact
Abstract: The symmetries of a polygon form a group. This group acts on the polygon by rotating it and flipping it. This basic idea of studying a group as symmetries of an object extends far beyond polygons. Through a myriad of colorful pictures, I will introduce the notion of a group, some of my favorite examples, & then examples of the interplay between these groups & various geometric objects. No advanced mathematical knowledge will be assumed and of course we will also play with doughnuts!
Refreshments will be served at 4:15 pm in Seeley Mudd 208.
Feng Hu '19
Robert Zielinski '19
Zachary Brown '19
Caroline MacGillivray '19
Kate Finnerty '19
Ellie Thieu '19
Gregory Caroll '19
Title: Chip-firing games on graphs
Title: Pizza Numbers!
Abstract: Our goal is to experience firsthand the joy, frustration, and creativity involved in exploring a question as a mathematician does. We’ll begin with a simple puzzle: If we slice a pizza with n straight line cuts, what is the maximum number of pieces we can make? Discovering these pizza numbers will inspire us to ask a variety of related questions, some of which we’ll answer and others of which will lead to unsolved problems at the level of current mathematical research!
Refreshments will be served at 4:00 pm in Seeley Mudd 208.
Talk by Matteo Riondato, who will join Amherst as an Assistant Professor in January 2019
Title: "Data Mining: Tasks, Systems, Challenges, and Research Directions"
Abstract: In this talk, I describe the field of Data Mining (DM) from the point of view of a researcher in this discipline. Starting from my definition of DM, I give examples of DM tasks for different kinds of data, commenting on available systems for DM and discussing the algorithmic challenges in DM. I show how my research tackles some of these challenges and list the interesting questions I plan to answer in the near future with the help of Amherst students.
Title: The Moduli of Space Curves
Abstract: I will give a prerequisite-free introduction to the idea of a moduli space. Then I'll introduce the moduli space of algebraic curves of genus g, a space that has connections to many areas of mathematics and has been studied intensively, yet remains mostly a mystery. In recent joint work with Søren Galatius and Sam Payne, we obtained new results on the cohomology of Mg
Refreshments will be served at 4:00 pm in Seeley Mudd 208.
Title: Inference from Multivariate Respondent-Driven Sampling Data
Abstract: Respondent-Driven Sampling is type of link-tracing network sampling used to study hard-to-reach populations. Beginning with a convenience sample, each person sampled is given 2-3 uniquely identified coupons to distribute to other members of the target population, making them eligible for enrollment in the study. This is effective at collecting large diverse samples from many populations. Due to the complexity of the sampling process, inference for the most fundamental of population features: population proportion, is challenging, and has been the subject of much work in recent years, typically using only data on local network size and the variable of interest. This talk focuses on work that considers inferential goals addressed using multiple variables measured on participants. We describe using data on local network composition for a variable biasing recruitment to adjust for preferential recruitment, semi-parametric testing for bivariate associations in the RDS dataset, and methods for clustering RDS participants based on covariate and referral data.
Refreshments will be served at 4:00 pm in Seeley Mudd 208.
Title: Discontinuous functions as limits of compactly supported formulas
Abstract: A bounded real valued function with domain the entire real numbers and one point of discontinuity can be discontinuous in six ways. In beginning textbooks such functions are usually defined piecewise with each piece being given by a formula. Here we give six examples, each having a different type of discontinuity at its unique point of discontinuity. Each example type is represented as a pointwise limit of quite simple continuous functions. Each approximating function can be given by an elementary formula and also can be chosen to be of compact support. (A function has compact support if the set of points where it is non-zero is contained in some finite interval.)
Refreshments will be served at 4:00 pm in Seeley Mudd 208.
Title: Data Science for Political Campaigns
STATFEST 2018 is a one day conference aimed at encouraging undergraduate students from historically underrepresented groups (African American, Hispanic, Native Americans) to consider careers and graduate studies in the statistical and data sciences. It includes presentations from established professionals, academic leaders, and current graduate students that will help attendees understand the opportunities and routes for success in the field. Many opportunities for networking will be created. Attendees are also encouraged to submit poster presentations. Panel forums provide information and tips for a rewarding graduate student experience, achieving success as an academic statistician or data scientist, and opportunities in the private and government arenas, among other topics.
StatFest 2018 will be taking place on Saturday, September 22nd. We are excited that StatFest 2018 will be held at Amherst College. Registration is free (but preregistration is required). More information can be found at: https://nhorton.people.amherst.edu/statfest.
The MAA Instructional Practices Guide: A Resource for Change
Abstract: The MAA Instructional Practices Guide presents evidence-based
methods for engaging students. Beyond documenting active-learning
classroom strategies, the guide also includes practices for assessment
and course design that support these strategies. This presentation will,
of course, include an overview of the guide, but be sure to bring a
pencil. Throughout the period, we will be putting some of the practices
into, well, practice.
Refreshments at 4 pm in SM 208
Searchable calendar of events in the Five College area.
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