New Major in Statistics at Amherst College
To meet the educational needs of our students and address the growing demand and interest in the area of Statistics, Amherst College has created a new major in Statistics as part of a newly renamed Department of Mathematics and Statistics. The new major will help students develop the capacity to turn data into information that can be used to guide decision-making. The new major consists of foundational courses in mathematics and computer science, along with a series of introductory, intermediate and advanced courses in statistics, culminating in a capstone course (Advanced Data Analysis) and a comprehensive evaluation of a project. More information can be found at the department's website or in this article in the student newspaper.
Pioneers in Civic Data: Breaking into the Open(Data) and other lessons on approaching a new frontier
- Logan Werschky (Smith '04), Special Advisor to NYC's Chief Data Analytics Officer
- Monday, April 28th, 2:40 - 4 pm
- Smith College, Weinstein Auditorium, Wright Hall
- This talk comes to us through the Landscape Studies Speakers Program at Smith College
Announcing the Five College DataFest
We are happy to announce that the Five College DataFest, sponsored in part by the Five College Statistics Program, will be held the weekend of March 29th and 30th at the University of Massachusetts in Amherst. DataFest is a nationally-coordinated competition that challenges undergraduates working in teams of up to five to extract meaningful insights from a rich and complex data set. A number of prizes will be awarded, including: "Best in Show", "Best Visualization", and "Best Use of External Data". Previous DataFests held at UCLA and Duke University have drawn large numbers of students, and we are hoping for a great turnout from the Five Colleges: Amherst, Hampshire, Mount Holyoke, and Smith Colleges, as well as UMass. Sponsorships opportunities are available -- please contact Ben Baumer (email@example.com) or Andrew Bray (firstname.lastname@example.org) for more information.
Inferring Causation without Randomization: A matched design to assess the number of embryos to transfer during in vitro fertilization
- Cassandra Pattanayak, Wellesley College
- Monday, September 23rd -- talk at 4:00pm with refreshments at 3:30pm
- Amherst College, Seeley Mudd room 206
Transferring one rather than two embryos during in vitro fertilization has been endorsed as a way to reduce multiple birth rates, but no large-scale randomized trial has evaluated the impact of the number of embryos transferred on birth outcomes. This presentation describes the design of a non-randomized study that parallels a hypothetical randomized experiment to examine the effect of single versus double embryo transfer. Using national surveillance data from the Centers for Disease Control and Prevention, single and double embryo cycles were paired on estimated propensity scores to create matched treated and control groups that are as similar on the observed background covariates as if the number of embryos transferred had been randomly assigned. This example illustrates a general framework for drawing causal rather than associative inferences from non-randomized studies, and the crucial role of checking balance between treatment and control groups on key background covariates is emphasized.
Big Data: A perspective on their current uses and potential future uses by the Federal Statistical System
- Mike Horrigan, Associate Commissioner for Prices and Living Conditions, Bureau of Labor Statistics, Washington, DC
- Monday, September 30th talk at 4:30pm with tea at 4:00pm
- Smith College Ford Hall room 240
This talk will explore the world of big data in terms of how they are currently used by the Federal Statistical system and explore possible ways in which big data sources may be leveraged in the future. In an era of declining real budgets for the Federal Statistical agencies, big data are often seen as an efficient and economical way to replace or supplement existing data collection programs. However, the blending of existing Federal data series collected using established statistical survey practices with big data sources that are not necessarily representative samples of a larger universe frame poses some significant challenges to the Federal statistical system, especially in terms of the quality tradeoffs we may be making. We also face challenges in maintaining our goal of methodological transparency when the potential biases of some big data sources are not always well understood. The talk begins with an attempt to define big data. I then present the results (to date) of an environmental scan we are conducting on the uses of big data across Federal statistical agencies as well as a scan of big data uses in academia and private business. The remainder of the talk addresses the issue of the potential future uses of big data, developing a perspective based on existing frameworks for judging the quality of economic statistics as well as looking at the statistical issues associated with blending survey based data with big data sources. I am particularly interested in your thoughts on the statistical issues and potential solutions to such issues posed by blended statistics. I end the seminar with concluding thoughts on the future of big data in the Federal Statistical system based on my role as a Director of several major statistical survey programs.
This talk reflects the current status of a project being sponsored by the American Economic Association Data Subcommittee on Big Data, for which I am a co-chair along with Ana Aizcorbe of the Bureau of Economic Analysis. The goal of the project is to report on the current and potential uses of big data across the Federal Statistical system.
The talk is part of the activities of the International Year of Statistics and is sponsored by the Departments of Mathematics and Statistics as well as Economics at Smith College and co-sponsored by the Five College Statistics Program and the Boston Chapter of the American Statistical Association.
For more information about the talk, contact Katherine Halvorsen (email@example.com, 413-585-3874). More information about Mike Horrigan can be found here:
On the weekend of June 1st, 2013, web and software developers, designers, community organizers, and other folks from all over Western Mass will gather to tackle local challenges with technology -- sponsored in part by the Five College Statistics Program.
International Year of Statistics Talk
Application Deadline : 2012/12/03